Publicaciones
Stehlík, Milan; Marek, Jaroslav; Núnez Soza, Ludy; Stehlíková, Silvia; Pozdılková, Alena; Rios Núnez, Catalina (2024). On sensitivity analysis for Fisher-Behrens comparisons of soil contaminants in Arica, Chile. Stochastic Analysis and Applications, 1–22. https://www.tandfonline.com/doi/full/10.1080/07362994.2024.2370960
Danilo Leal, Luboš Střelec, Felix Fuders, Milan Stehlík, M. (2024). On testing the changes in trends of stock market index and rates. Communications in Statistics – Simulation and Computation, 1–28. https://doi.org/10.1080/03610918.2024.2376874
Milan Stehlik, Weng Kee Wong, Ping-Yang Chen, Jozef Kiselak, A Double Exponential Particle Swarm Optimization with non-uniform variates as stochastic tuning and guaranteed convergence to a global optimum with sample applications to finding optimal exact designs in biostatistics,
Applied Soft Computing, https://doi.org/10.1016/j.asoc.2024.111913
Neaman, A., Navarro-Villarroel, C., Poblete-Ramos, F., Lizardi, N., Burnham, E., Huerta-Salinas, O., Zabel, S., Ermakiv, D., Castro, M., Otto, S. (2024). Reconciling the soil stewardship paradox: Knowledge without care, care without knowledge. Geoderma, v.37. https://doi.org/10.1016/j.geodrs.2024.e00794
Contreras-Ruston, F., Castillo-Allendes, A., Saavedra-Garrido, J., Ochoa-Munoz, AF., Hunter, E.J., Kotz, S.A., Navarra, J. (2024). Voice self-assessment in individuals with Parkinson’s Disease compared to general voice disorders. Parkinsonism and Related Disorders 123, 106944. DOI: https://doi.org/10.1016/j.parkreldis.2024.106944
Kharazmi, O., Contreras-Reyes, J.E. (2024). Belief inaccuracy information measures and their extensions. Fluctuation and Noise Letters 23, 2450041. DOI: https://doi.org/10.1142/S021947752450041X
Kharazmi, O., Contreras-Reyes, J.E., Basirpour, M.B. (2024). Jensen-variance distance measure: A unified framework for statistical and information measures. Computational and Applied Mathematics 43, 144. DOI: https://doi.org/10.1007/s40314-024-02666-x
Kharazmi, O., Contreras-Reyes, J.E. (2024). Fractional cumulative residual inaccuracy information measure and its extensions with application to chaotic maps. International Journal of Bifurcation and Chaos 34(1), 2450006. DOI: https://doi.org/10.1142/S0218127424500068
Prieur-Coloma, Y., Torres, F., Guevara, P., Contreras-Reyes, J.E., El-Deredy, W. (2024). Gaussian Processes Spectral Kernels Recover Features of Metastable Oscillatory Modes in Human-Connectome-Coupled Model of the Brain. 2023 19th International Symposium on Medical Information Processing and Analysis (SIPAIM). DOI: http://dx.doi.org/10.1109/SIPAIM56729.2023.10373531
R. Ecklmair, C. Ibacache Quiroga, A. Dinamarca, J. Kiselak, B. Barraza, M. Stehlik, On statistical analysis for complex neural networks: modelling and prediction, Stochastic Analysis and Applications, https://doi.org/10.1080/07362994.2023.2295248
Neaman, A., Montero, E., Pensini, P., Burnham, E., Castro, M., Ermakov, D.S., Navarro-Villarroel, C. (2023). Unleashing the Power of Connection: How Adolescents’ Prosocial Propensity Drives Ecological and Altruistic Behaviours. Sustainability, v.15, 8070. https://doi.org/10.3390/su15108070
Neaman, A. Zakharikhina, L., Navarro-Villarroel, C., Peñaloza, P., Dovletyarova, E. (2023). Choosin your procedure wisely: Removal of outliers is inappropriate for estimating background concentrations of trace elements in soil. Environmental Toxicology and Chemistry, 42(3). https://doi.org/10.1002/etc.5550
Contreras-Reyes, J.E., Maleki, M. (2023). Parameter estimation of the multivariate unrestricted skew-normal distribution using ECM algorithm. Communications in Statistics: Simulation and Computation. DOI: https://doi.org/10.1080/03610918.2023.2289360
M. Stehlik, K. J. Bal, K. Pant, S. Stehlíková, L. N. Soza, Statistical analysis for the water quality of rivers of Uttarakhand, India, AIP Conf. Proc. 2953, 030004 (2023), https://doi.org/10.1063/5.0177425
Contreras-Reyes, J.E., Kharazmi, O. (2023). Belief Fisher-Shannon information plane: Properties, extensions, and applications to time series analysis. Chaos, Solitons & Fractals 177, 114271. DOI: https://doi.org/10.1016/j.
Leal, D., Jimenez, R., Riquelme, M., Leiva, V., 2023. Elliptical capital asset pricing models: Formulation, diagnostics, case study with Chilean data, and economic rationale. Mathematics 11 (6):1394.DOI: https://www.mdpi.com/2227-7390/11/6/1394
Sánchez, L., Ibacache-Pulgar G., R., Marchant, C., Riquelme, M., 2023. Modeling Environmental Pollution Using Varying-Coefficients Quantile Regression Models under Log-Symmetric Distributions. Axioms 12 (10):976.https://doi.org/10.3390/axioms12100976
Cesar A. Valdivia-Carrera, Ana C. Ho-Palma, Astrid Munguia-Mercado, Karoll Gonzalez-Pizarro, Claudia Ibacache-Quiroga, Alejandro Dinamarca, Milan Stehlík, Marta Rusiñol, Rosina Girones, Maria T. Lopez-Urbina, Anani Basaldua Galarza, Eloy Gonzales-Gustavson 2023, Surveillance of SARS-CoV-2, rotavirus, norovirus genogroup II, and human adenovirus in wastewater as an epidemiological tool to anticipate outbreaks of COVID-19 and acute gastroenteritis in a city without a wastewater treatment plant in the Peruvian Highlands, Science of the Total Environment, https://doi.org/10.1016/j.
Stehlík, M., Ibacache-Quiroga, C., Dinamarca, A.M., Gonzalez-Pizarro, K., Valdivia-Carrera, C.A., Gonzales-Gustavson, E., Ho-Palma, A. C., Barraza-Morales, B. 2023 “On asymmetric relations and robustified cross-correlation approach to surveillance based on detection of SARS-CoV-2 in wastewater in Chile and Peru”. Chemometrics and Intelligent Laboratory Systems, DOI: https://doi.org/10.1016/j.
Kharazmi, O., Contreras-Reyes, J.E. (2023). Deng-Fisher information measure and its extensions: Application to Conway’s Game of Life. Chaos, Solitons & Fractals 174, 113871. DOI: https://doi.org/10.1016/j.chaos.2023.113871
Ochoa-Muñoz, A.F., Contreras-Reyes, J.E. (2023). Multiple Factor Analysis Based on NIPALS Algorithm to Solve Missing Data Problems. Algorithms 16(10), 457. DOI: https://doi.org/10.3390/a16100457
Ubal, C., Di Giorgi, G., Contreras-Reyes, J.E., Salas, R. (2023). Predicting the long-term dependencies in Time Series using Recurrent Artificial Neural Network. Machine Learning & Knowledge Extraction 5(4), 1340-1358. DOI: https://doi.org/10.3390/make5040068
Kuschel, K., Carrasco, R., Idrovo-Aguirre, B. J., Duran, C., Contreras-Reyes, J.E. (2023). Preparing Cities for Future Pandemics: Unraveling the Influence of Urban and Housing Variables on COVID-19 Incidence in Santiago de Chile. Healthcare 11(16), 2259. DOI: https://doi.org/10.3390/healthcare11162259
Milan Stehlík, Jozef Kiseľák & Jiří Dušek , (2023). Über die Dynamik von Ökosystemen zur Erhaltung von Feuchtgebieten und Wäldern. In: Fuders, F., Donoso, P.J. (eds) Ökologisch-ökonomische und sozioökologische Strategien zur Erhaltung der Wälder . Springer, Cham. https://doi.org/10.1007/978-3-
P. K. Jordanova, M. Savov, A. Tchorbadjieff, M. Stehlik, Mixed Poisson process with Stacy mixing variable, Stochastic Analysis and Applications, https://arxiv.org/abs/2303.10226, https://doi.org/10.1080/07362994.2023.2242471
Stromberg, A. J., Chen, J., Oliveira, T, Yichuan, Z., Moghaddass, R., Stehlik,M., Editorial to the special issue: Statistical Perspectives on Analytics for COVID-19 Data, Journal of Applied Statistics, Volume 50, 2023 – Issue 11-12 https://www.tandfonline.com/
Contreras-Reyes (2023). Information quantity evaluation of multivariate SETAR processes of order one and applications. Statistical Papers. DOI: https://doi.org/10.1007/s00362-023-01457-6
Kharazmi, O., Contreras-Reyes, J.E., Balakrishnan, N. (2023). Jensen-Fisher information and Jensen-Shannon entropy measures based on complementary discrete distributions with an application to Conway’s game of life. Physica D: Nonlinear Phenomena. DOI: https://doi.org/10.1016/j.physd.2023.133822
Kharazmi, O., Jamali, H., Contreras-Reyes, J.E. (2023). Fisher information and its extensions based on Infinite mixture density functions. Physica A: Statistical Mechanics and its Applications. DOI: https://doi.org/10.1016/j.physa.2023.128959
Troncoso, N., Contreras-Reyes, J.E., Idrovo-Aguirre, B.J. (2023). Measuring economic uncertainty synchrony with cross-sample entropy under common external factors: the case of Chile. Fluctuation and Noise Letters 22(6), 2350046. DOI: https://doi.org/10.1142/S0219477523500463
Saavedra-Nievas, J. C., Nicolis, O., Galea, M., & Ibacache-Pulgar, G. (2023). Influence diagnostics in Gaussian spatial–temporal linear models with separable covariance. Environmental and Ecological Statistics. DOI: https://doi.org/10.1007/s10651-023-00556-9
Di-Giorgi, G., Salas, R., Avaria, R., Ubal, C., Rosas, H., & Torres, R. (2023). Volatility forecasting using deep recurrent neural networks as GARCH models. Computational Statistics. DOI: https://doi.org/10.1007/s00180-023-01349-1
Aguilera-Bohórquez, B., Corea, P., Sigüenza, C., Gerstner-Saucedo, J., Carvajal, A., & Cantor, E. (2023). Relationship between Spinopelvic Parameters and Hip Function in Patients with Femoroacetabular Impingement at Diagnosis: A Cross-Sectional Study. Hip & Pelvis, 35(1), 6. DOI: https://doi.org/10.5371%2Fhp.2023.35.1.6
Celorio, W., Cifuentes, L., Cantor, E., & Wagner, A. (2023). Thyroid function and thyroid antibodies in patients with alopecia areata: a comparison of clinical patterns. Anais Brasileiros de Dermatologia (Portuguese). DOI: https://doi.org/10.1016/j.abd.2022.10.007
Plaza, F., Araya, H., & Yáñez, E. (2023). Environmental effect on the variability of anchovy (Engraulis ringens) in northern Chile: Autoregressive conditional heteroskedastic approach with exogenonus variable and missing values. Fisheries Research, 260, 106607. DOI: https://doi.org/10.1016/j.fishres.2022.106607
Aldana alberici Adam, Gunther F. Avila Marín, Alejandra Christen and Lydia Sonia Cidale. Synthetic Light Curve Design for Pulsating Binary Stars to Compare the Efficiency in. The Detection of Periodicities. https://www.mdpi.com/2075-4434/11/3/69
P. Jordanova, M. Stehlik, Flexible extreme value inference, Stochastic Analysis and Applications Article doi: 10.1080/07362994.2023.2213745 https://doi.org/10.1080/07362994.2023.2213745
Neaman, A., Montero, E. Pensini P., Burnham E., Castro, M., Ermakov, D., Navarro-Villarroel, C. (2023). Unleashing the Power of Connection: How Adolescents’ Prosocial Propensity Drives Ecological and Altruistic Behaviours. Sustainability (15). https://doi.org/10.3390/su15108070
Zachary R. Kuenstler, Brennan C. Merley, Milan Stehlik, Jerzy Filus, Lidia Filus, Claudia Navarro, Jean Paul Maidana and Felix Fuders, On some consequences of COVID-19 in EUR/USD exchange rates and economy (2023), Springer Volume, Icra9, 1-11.
Flournoy, N., Hearne, L., Kiselak, J., Stehlik, M. On dose response modelling for evaluation of drugs combinations, Stochastic Analysis and Applications,DOI: 10.1080/07362994.2023.2170885 https://doi.org/10.1080/07362994.2023.2170885
Grilo, L.M., Pereira, E., Jean, P.M., Stehlik, M., On stochastic aspects of impact modeling of the innovation incentive system and business internationalization: evidence from Portuguese SMEs, Stochastic Analysis and Applications, https://doi.org/10.1080/07362994.2023.2166532
Lu, M., Cavieres, J., Moraga, P. (2023). A Comparison of Spatial and Nonspatial Methods in Statistical Modeling of NO2: Prediction Accuracy, Uncertainty Quantification, and Model Interpretation. Geographical Analysis. DOI: https://doi.org/10.1111/gean.12356
Stehlik, M., Leal D., Kiselak, J., Leers,J., Strelec, L., Fuders, F. (2023)
Stochastic approach to heterogeneity in short-time announcement effects on the Chilean stock market indexes within 2016-2019, Stochastic Analysis and Applications, DOI: https://doi.org/10.1080/07362994.2022.2164508
Contreras-Reyes, J.E. (2023). Information quantity evaluation of nonlinear time series processes and applications. Physica D: Nonlinear Phenomena 445, 133620. DOI: https://doi.org/10.1016/j.physd.2022.133620
Kharazmi, O., Contreras-Reyes, J.E., Balakrishnan, N. (2023). Optimal information, Jensen-RIG function and $\alpha$-Onicescu’s correlation coefficient in terms of information generating functions. Physica A: Statistical Mechanics and its Applications 609, 128362. DOI: https://doi.org/10.1016/j.physa.2022.128362
Contreras-Espinoza, S., Caamaño-Carrillo, C., Contreras-Reyes, J.E. (2023). Generalized autoregressive score models based on sinh-arcsinh distributions for time series analysis. Journal of Computational and Applied Mathematics 423, 114975. DOI: https://doi.org/10.1016/j.cam.2022.114975
Chávez, D., Contreras-Reyes, J.E., Idrovo-Aguirre, B.I. (2023). A threshold GARCH model for the Chilean economic uncertainty. Journal of Risk and Financial Management 16(1), 20. DOI: https://doi.org/10.3390/jrfm16010020
Martínez-Arroyo, A., Cantor, E., Fisberg, R., & Corvalán, C. (2022). Lower adherence to a prudent dietary pattern is associated with earlier age at menarche in adolescents from the Growth and Obesity Chilean Cohort Study. Frontiers in Public Health, 10, 5464. DOI: https://doi.org/10.3389/fpubh.2022.995593
Martínez, S., Ron-Translateur, T., Cantor, E., & Palacio, J. C. (2022). Resuperficialización de la rótula en el reemplazo primario total de rodilla: estudio comparativo a dos años de seguimiento. Revista de la Asociación Argentina de Ortopedia y Traumatología, 87(6), 798-803. DOI: https://doi.org/10.15417/issn.1852-7434.2022.87.6.1453
Mantilla, M., Stangl-Correa, P., Stangl-Herrera, W., Cantor, E., Echeverry-Vélez, A., & Palacio, J. C. (2022). Validación al español del instrumento Self-Administered Patient Satisfaction Scale (SAPS) para reemplazo total de cadera o de rodilla. Revista de la Asociación Argentina de Ortopedia y Traumatología, 87(6), 765-771. DOI: https://doi.org/10.15417/issn.1852-7434.2022.87.6.1535
Aguilera-Bohórquez, B., Juárez, O., Calvache, D., Cantor, E., Navarro, H., Vélez, J., & Pachón-Vásquez, M. (2022). Groin pain of neurological origin as a differential diagnosis of femoroacetabular impingement. HIP International, 11207000221135067. DOI: https://doi.org/10.1177/11207000221135067
Guerrero, M. P., Romero, A. F., Luengas, M., Dávalos, D. M., Mesa-Monsalve, J. G., Vivas-Trochez, R., … & López Medina, E. (2022). Etiology and risk factors for admission to the pediatric intensive care unit in children with encephalitis in a developing country. The Pediatric Infectious Disease Journal, 41(10), 806-812. DOI: https://doi.org/10.1097/INF.0000000000003637
Gonzalez, E. G., Orejuela, J. M., Banguera, J. S., Moreno, D. C., Narváez, G. O., Muñoz, A. O., & Rodriguez, C. M. (2022). Ecology and population dynamics of yeast starter cultures in cocoa beans fermentation. BioTechnologia, 103(4), 343-353. DOI: https://doi.org/10.5114/bta.2022.120704
Neaman, A., Zakharikhina, L., Navarro-Villarroel, C., Peñaloza, P., Dovletyarova, E. (2022). “Choose your procedure wisely: Removal of outliers is inappropriate for estimating background concentrations of trace elements in soil”. Environmental Toxicology and Chemistry. https://doi.org/10.1002/etc.5550
Stehlik, M. Editorial, Research in Statistics, DOI: https://doi.org/10.1080/27684520.2022.2136508
Sanzana-Luengo, C., Díaz, L., Abarza, L., Alvarado, E., Beltrán, V. (2022). Teledentistry protocol for the elderly in the context of the COVID-19 pandemic through a web platform/mobile app: approach from the general dentist. Journal of Oral Research, S1, 1-8. DOI: http://dx.doi.org/10.17126/joralres.2022.026
Beltrán, V., Mardones, P. A., Díaz, J., Alvarado, E., von Marttens, A. (2022). TEGO: A new concept of teledentistry for the elderly through a web platform and mobile app in the context of the covid-19 pandemic. Journal of Oral Research, S1, 1-8. DOI: http://dx.doi.org/10.17126/joralres.2022.023
Beltrán, V., von Marttens, A., Acuña-Mardones, P., Sanzana-Luengo, C., Rueda-Velásquez, S.J., Alvarado, E., …, Venegas, B. (2022). Implementation of a Teledentistry Platform for Dental Emergencies for the Elderly in the Context of the COVID-19 Pandemic in Chile. BioMed Research International 2022, 6889285. DOI: https://doi.org/10.1155/2022/6889285
Bitcoin Here, Bitcoin There, Bitcoin Everywhere Nonetheless Where Are the (Negative) Interest Rates? M. Schullitsch, M. Striedner, V. Mühlbacher, D. Silian, Pavicic,D. Ljubijankic,M. Nagy, E. Hodzic, K. Hauer, J. Kise˘lák, and M. Stehlík https://aip.scitation.org/doi/abs/10.1063/5.0101120
Neaman, A., Pensini, P., Zabel, S., Otto, S., Ermakov, D.S., Dovletyarova, E.A., Burnham, E., Castro, M., Navarro-Villarroel, C. (2022). The Prosocial Driver of Ecological Behavior: The Need for an Integrated Approach to Prosocial and Environmental Education. Sustainability 14(7). https://doi.org/10.3390/su14074202. Q2
Contreras-Reyes, J.E., Gallardo, D.I., Kharazmi, O. (2022). Time-dependent residual Fisher information and distance for some special continuous distributions. Communications in Statistics – Simulation and Computation. DOI: https://doi.org/10.1080/
Ochoa-Muñoz, A.F., Peña-Torres, J.A., García-Bermúdez, C.E., Mosquera-Muñoz, K.F., Mesa-Diez, J. (2022). On characterization of sensory data in presence of missing values: The case of sensory coffee quality assessment. Ingeniare. Revista chilena de ingeniería 30(3), 564-573. DOI: http://dx.doi.org/10.4067/
Mahdavi, A., Kharazmi, O., Contreras-Reyes, J.E. (2022). On the contaminated weighted exponential distribution: Applications to modeling insurance claim data. Journal of Risk and Financial Management 15(11), 500. DOI: https://doi.org/10.3390/jrfm15110500
Jeldes, N., Ibacache-Pulgar, G., Marchant, C., López-Gonzales, J.L. (2022). Modeling Air Pollution Using Partially Varying Coefficient Models with Heavy Tails. Mathematics 10(19), 3677. DOI: https://doi.org/10.3390/math10193677
Nicolis, O., Riquelme Quezada, L.M., Ibacache-Pulgar, G. (2022). Temporal Cox Process with Folded Normal Intensity. Axioms 11(10), 513. DOI: https://doi.org/10.3390/axioms11100513
Marmolejo-Ramos, F., Tejo, M., Brabec, M., Kuzilek, J., Joksimovic, S., Kovanovic, V., GonzÁlez, J., Kneib, T., Bühlmann, P., Kook, L., Briseño-Sánchez, G., & Ospina, R. (2022). Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics. WIREs Data Mining and Knowledge Discovery, e1479. https://doi.org/10.1002/widm.
Pérez-Aros, P., Quiñinao, C. & Tejo, M. Control in Probability for SDE Models of Growth Population. Appl Math Optim 86, 44 (2022). https://doi.org/10.1007/s00245-022-09915-7
Bitcoin Here, Bitcoin There, Bitcoin Everywhere Nonetheless Where Are the (Negative) Interest Rates? M. Schullitsch, M. Striedner, V. Mühlbacher, D. Silian, Pavicic,D. Ljubijankic,M. Nagy, E. Hodzic, K. Hauer, J. Kise˘lák, and M. Stehlík https://aip.scitation.org/doi/abs/10.1063/5.0101120
M. Stehlik, C. Navarro, P. Ganske, J. Kimmel, J. Koffler, E. Mistlberger, V. Wimmer, E. Zeintl, 2021, On the symbiotic relationships between South American Sea lions and Humans, Chapter in “Climate Crisis & Creation Care Eco-Economic Sustainability, Ecological Integrity And Justice” 331-350, ISBN (10): 1-5275-7420-2 ISBN (13): 978-1-5275-7420-5, Editor: Prof. Christina Nellist, Cambridge Scholars Publishing.
Milan Stehlik, Jiri Dusek, Jozef Kiselak, Alexander Brandmayr, Birgit Grubauer, Julia Haider, Roman Pfeiler, Stefan Raidl, Anika Schindlauer, Alexandra Stadler, 2021, Recurrence Analysis of Methane Emissions from Wetland Ecosystem, Chapter in “Climate Crisis & Creation Care Eco-Economic Sustainability, Ecological Integrity And Justice” 308-328, ISBN (10): 1-5275-7420-2 ISBN (13): 978-1-5275-7420-5, Editor: Dr. Christina Nellist, Cambridge Scholars Publishing, https://www.cambridgescholars.com/product/978-1-5275-7420-5.
Kharazmi, O., Alizadeh, M., Contreras-Reyes, J.E., Haghbin, H. (2022). Arctan-based family of distributions: Properties, survival regression, Bayesian analysis and applications. Axioms 11(8), 399. DOI: https://doi.org/10.3390/axioms11080399
Contreras-Reyes, J.E. (2022). Mutual information matrix based on Rényi entropy and application. Nonlinear Dynamics. DOI: https://doi.org/10.1007/s11071-022-07665-3
Cantor, E., Salas, R., Torres, R. (2022). Femicide and Attempted Femicide before and during the COVID-19 Pandemic in Chile. International Journal of Environmental Research and Public Health 19(13), 8012. DOI: https://doi.org/10.3390/ijerph19138012
Cavieres, J., Ibacache-Pulgar, G., Contreras-Reyes, J.E. (2022). Thin plate spline model under skew-normal random errors: estimation and diagnostic analysis for spatial data. Journal of Statistical Computation and Simulation. DOI: https://doi.org/10.1080/00949655.2022.2090564
Ibacache-Pulgar, G., Villegas, C., López-Gonzales, J.L. Moraga, M. (2022). Influence measures in nonparametric regression model with symmetric random errors. Statistical Methods & Applications. DOI: https://doi.org/10.1007/s10260-022-00648-z
Contreras-Reyes, J.E. (2022). Rényi entropy and divergence for VARFIMA processes based on characteristic and impulse response functions. Chaos, Solitons & Fractals 160, 112268. DOI: https://doi.org/10.1016/j.chaos.2022.112268
Leite Coelho da Silva, F., da Costa, K., Canas Rodrigues, P., Salas, R., López-Gonzales, J.L. (2022). Statistical and Artificial Neural Networks Models for Electricity Consumption Forecasting in the Brazilian Industrial Sector. Energies, 15(2), 588. DOI: https://doi.org/10.3390/en15020588
López-Medina, E., Camacho-Moreno, G., Brizuela, M. E., Dávalos, D.M., Torres, J. P., Ulloa-Gutierrez, R., …, Cantor, E., Asturias, E.J. (2022). Factors Associated With Hospitalization or Intensive Care Admission in Children With COVID-19 in Latin America. Frontiers in Pediatrics, 459. DOI: https://doi.org/10.3389/fped.2022.868297
Valderrama, L.A., Barrera, L., Cantor, E.J., Muñoz, J., Arango, J., Tobon, C., Canaud, B. (2022). Mortality in High-Flux Hemodialysis vs. High-Volume Hemodiafiltration in Colombian Clinical Practice: A Propensity Score Matching Study. Kidney and Dialysis, 2(2), 209-220. DOI: https://doi.org/10.3390/kidneydial2020022
Stehlik, M., Sabolova, R., Seckarova, V., Nuñez-Soza, L., Kiselak, J. I-divergence based statistical inference for heteroscedasticity and compounds of arsenic contamination in Chile, Chemometrics and Intelligent Laboratory Systems, https://doi.org/10.1016/j.chemolab.2022.104579
Caamaño-Carrillo, C., Contreras-Reyes, J.E. (2022). A Generalization of the Bivariate Gamma Distribution Based on Generalized Hypergeometric Functions. Mathematics, 10, 1502. DOI: https://doi.org/10.3390/math10091502
Contreras-Reyes, J.E. (2022). Information-theoretic aspects of location parameter estimation under skew-normal settings. Entropy 24(3), 399. DOI: https://doi.org/10.3390/e24030399
Rodríguez, K.M., Bossy, M., Henry, C. (2022). Particle agglomeration in flows: fast data-driven spatial decomposition algorithm for CFD simulations. International Journal of Multiphase Flow 149, 103962. DOI: https://doi.org/10.1016/j.ijmultiphaseflow.2021.103962
Bossy, M., Jabir, J.F., Rodriguez, K.M. (2022). Instantaneous turbulent kinetic energy modelling based on Lagrangian stochastic approach in CFD and application to wind energy. Journal of Computational Physics, 110929. DOI: https://doi.org/10.1016/j.jcp.2021.110929
M. Stehlik , J. Kiselak, A. Dinamarca, E. Alvarado, F. Plaza, F.A. Medina, S. Stehlikova, J. Marek, B. Venegas, A. Gajdos, Y. Li, S. Katuscak, A. Brazinova, Y. Lu (2022) REDACS: Regional emergency driven adaptive cluster sampling for effective COVID-19 management, Stochastic Analysis and Applications, DOI: https://doi.org/10.1080/07362994.2022.2033126
Querales, M., Salas, R., Morales, Y., Allende-Cid, H., & Rosas, H. (2022). A stacking neuro-fuzzy framework to forecast runoff from distributed meteorological stations. Applied Soft Computing, 108535. DOI: https://doi.org/10.1016/j.asoc.2022.108535
Contreras-Reyes, J.E., Brito, A. (2022). Refined cross-sample entropy based on Freedman-Diaconis rule: Application to foreign exchange time series. Journal of Applied and Computational Mechanics. DOI: https://dx.doi.org/10.22055/jacm.2022.39470.3412
Neaman, A., Diaz-Siefer, P., Burnham, E., Castro, M., Zabel, S., Dovletyarova, E.A., Navarro-Villarroel, C., Otto, S. (2021). Catholic religious identity, prosocial and pro-environmental behaviors, and connectedness to nature in Chile. Gaia-Ecological Perspectives for Science and Society 30(1): 44-50. https://doi.org/10.14512/gaia.30.1.9. Q3
Otto, S., Pensini, P., Zabel, S., Diaz-Siefer, P., Burnham, E., Navarro-Villarroel, C., Neaman, A. (2021). The prosocial origin of sustainable behavior: A case study in the ecological domain. Global Environmental Change-Human and Policy Dimensions 69. https://doi.org/10.1016/j.gloenvcha.2021.102312. Q1
Stuckey, J.W., Neaman, A., Verdejo, J., Navarro-Villarroel, C., Penaloza, P., Dovletyarova, E.A. (2021). Zinc Alleviates Copper Toxicity to Lettuce and Oat in Copper-Contaminated Soils. Journal of Soil Science and Plant Nutrition 21(2): 1229-1235. https://doi.org/10.1007/s42729-021-00435-x. Q1
Andrés Villaveces , Antonio Sanhueza , Carlos Felipe Henríquez Roldán , José Antonio Escamilla-Cejudo & Eugenia M. S. Rodrigues (2021). Transport modes and road traffic mortality in the Americas: Deaths among pedestrian and motorcycle users through the lifespan. International Journal of Injury Control and Safety Promotion. DOI: https://doi.org/10.1080/17457300.2020.1858112
Palmeiro-Silva, Y. K., Weinstein-Oppenheimer, C., Henríquez-Roldán, C.F. y Bangdiwala, S. I.. (2021). Alfabetización estadística y comunicación de riesgo para la vacunación contra la COVID-19: una revisión de alcance. Rev Panam Salud Publica 45, 2021 | www.paho.org/journal | https://doi.org/10.26633/RPSP.2021.108
Cordova, C.H., Portocarrero, M.N.L., Salas, R., Torres, R., Rodrigues, P.C., López-Gonzales, J.L. (2021). Air quality assessment and pollution forecasting using artificial neural networks in Metropolitan Lima-Peru. Scientific Reports, 11(1), 1-19. DOI: https://doi.org/10.1038/s41598-021-03650-9
Aguilera-Bohórquez, B., Pacheco, J., Castillo, L., Calvache, D., Cantor, E. (2021). Complications of hip endoscopy in the treatment of subgluteal space pathologies. Arthroscopy: The Journal of Arthroscopic & Related Surgery, 37(7), 2152-2161. DOI: https://doi.org/10.1016/j.arthro.2021.02.016
Chahuán-Jiménez, K., Rubilar-Torrealba, R., & Fuente-Mella, H.D.L. (2021). Market openness and its relationship to connecting markets due to covid-19. Sustainability, 13(19), 10964. DOI: https://doi.org/10.3390/su131910964
Fuente-Mella, H.D.L., Rubilar, R., Chahuán-Jiménez, K., & Leiva, V. (2021). Modeling COVID-19 cases statistically and evaluating their effect on the economy of countries. Mathematics, 9(13), 1558. DOI: https://doi.org/10.3390/math9131558
Cabrera-Paniagua, D., & Rubilar-Torrealba, R. (2021). Affective autonomous agents for supporting investment decision processes using artificial somatic reactions. Journal of Ambient Intelligence and Humanized Computing. DOI: https://doi.org/10.1007/s12652-021-03319-1
Cabrera-Paniagua, D., & Rubilar-Torrealba, R. (2021). A novel artificial autonomous system for supporting investment decisions using a Big Five model approach. Engineering Applications of Artificial Intelligence, 98, 104107. DOI: https://doi.org/10.1016/j.engappai.2020.104107
Cavieres, J., Monnahan, C. C., & Vehtari, A. (2021). Accounting for spatial dependence improves relative abundance estimates in a benthic marine species structured as a metapopulation. Fisheries Research 240, 105960. DOI: https://doi.org/10.1016/j.fishres.2021.105960
L. Salazar, S. Torres, J. Kiselak, F. Fuders, N. Ishimura, Y. Yoshizawa, M. Stehlik (2021),
Long memory estimation in a non-Gaussian bivariate process, Applied Mathematics and Computation, https://doi.org/10.1016/j.amc.2021.126871
I Araya, A Christen, M Curé, L S Cidale, R O J Venero, C Arcos, A C Gormaz-Matamala, M Haucke, P Escárate, H Clavería. Analytical solutions for radiation-driven winds in massive stars – II. The δ-slow regime. DOI:https://doi.org/10.1093/mnras/stab995
Alejandra Christen, M. Angélica Maulén-Yañez, Yoselinne Valencia, Eduardo González-Olivares, Diego F. Rial, Michel Curé. Linear incidence rate: Its influence on the asymptotic behavior of a stochastic epidemic model. DOI: http://dx.doi.org/10.1002/mma.6700
Idrovo-Aguirre, B.J., Contreras-Reyes, J.E. (2021). Monetary fiscal contributions to households and pension fund withdrawals during the COVID-19 pandemic: An approximation of their impact on construction labor supply in Chile. Social Sciences 10(11), 417. DOI: https://doi.org/10.3390/socsci10110417
Milan Stehlik, Jiri Dusek, Jozef Kiselak, Alexander Brandmayr, Birgit Grubauer, Julia Haider, Roman Pfeiler, Stefan Raidl, Anika Schindlauer, Alexandra Stadler, 2021, Recurrence Analysis of Methane Emissions from Wetland Ecosystem, Chapter in “Climate Crisis & Creation Care Eco-Economic Sustainability, Ecological Integrity And Justice” páginas 308-328, ISBN (10): 1-5275-7420-2 ISBN (13): 978-1-5275-7420-5, Editor: Dr. Christina Nellist, Cambridge Scholars Publishing.
Stehlik, M, J. Kiselak, Dinamarca, A. Li, Y. and Ying, Y. On covid19 outbreaks predictions: issues on stability, parameter sensitivity and precision, Stochastic Analysis and Applications, Volume 39 (3), 2021, Pages 383-404 DOI:
https://doi.org//0.1080/07362994.2020.1802291
Las actualizaciones son: Año 2021, Volumen 39(3), Páginas 383-404
J. Paseka, S. Solovjovs, and M. Stehlík (2021), Sugeno Integral Over Generalized Semi-quantales, B. Bede et al. (eds.), Fuzzy Information Processing 2020, Advances in Intelligent Systems and Computing 1337, https://doi.org/10.1007/978-3-030-81561-5_9
Milan Stehlik, Claudia Navarro, Patrick Ganske, Jasmina Kimmel, Julia Koffler, Elisabeth Mistlberger, Victoria Wimmer, Elias Zeintl, 2021, On the symbiotic relationships between South American Sea lions and Humans, Chapter in “Climate Crisis & Creation Care Eco-Economic Sustainability, Ecological Integrity And Justice” paginas 331-350, ISBN (10): 1-5275-7420-2 ISBN (13): 978-1-5275-7420-5, Editor: Dr. Christina Nellist, Cambridge Scholars Publishing.
Idrovo-Aguirre, B.J., Lozano, F.J., Contreras-Reyes, J.E. (2021). Prosperity or Real Estate Bubble? Exuberance Probability Index of Real Housing Prices in Chile. International Journal of Financial Studies 9(3), 51. DOI: https://doi.org/10.3390/ijfs9030051
Cantor, E., Salas, R., Rosas, H., Guauque-Olarte, S. (2021). Biological knowledge-slanted random forest approach for the classification of calcified aortic valve stenosis. BioData Mining volume 14, 35. DOI: https://doi.org/10.1186/s13040-021-00269-4
Chahuán-Jiménez, K., Rubilar, R., de la Fuente-Mella, H., Leiva, V. (2021). Breakpoint analysis for the COVID-19 pandemic and its effect on the stock markets. Entropy 23, 100. DOI: https://doi.org/10.3390/e23010100
Canessa, E., Chaigneau, S.E., Lagos, R., Medina, F.A. (2021). How to carry out conceptual properties norming studies as parameter estimation studies: Lessons from ecology. Behavior Research Methods 53, 354-370. DOI: https://doi.org/10.3758/s13428-020-01439-8
Héctor Araya, Natalia Bahamonde, Tania Roa & Soledad Torres (2021) Parameter estimation for a discrete time model driven by fractional Poisson process, Communications in Statistics – Theory and Methods, DOI: https://doi.org/10.1080/03610926.2021.1973504
Araya, H., Slaoui, M. & Torres, S. Bayesian inference for fractional Oscillating Brownian motion. Comput Stat (2021). https://doi.org/10.1007/s00180-021-01146-8
Ibacache-Pulgar, G., Figueroa-Zuñiga, J. and Marchant, C. (2021). Semiparametric Additive Beta regression models: Inference and Local Influence Diagnostic. REVSTAT-Statistical Journal, 19, 255-274. https://www.ine.pt/revstat/pdf/REVSTAT_v19-n2-05.pdf
Contreras-Reyes, J.E. (2021). Lerch distribution based on maximum nonsymmetric entropy principle: Application to Conway’s Game of Life cellular automaton. Chaos, Solitons & Fractals 151, 111272. DOI: https://doi.org/10.1016/j.chaos.2021.111272
Ramírez-Parietti, I., Contreras-Reyes, J.E., Idrovo-Aguirre, B.J. (2021). Cross-sample entropy estimation for time series analysis: a nonparametric approach. Nonlinear Dynamics. DOI: https://doi.org/10.1007/s11071-021-06759-8
H.araya and N. Bahamonde and L. Fermin and T. Roa and S. Torres (2021). On consistency of least square estimator in models sampled at random times driven by long memory noise: Renewal case. Statistica Sinica. doi: https://doi.org/10.5705/ss.202020.0457
H.araya and N. Bahamonde and L. Fermin and T. Roa and S. Torres (2021). On the consistency of least square estimator in models sampled at random times driven by long memory noise: The Jittered case. Statistica Sinica. doi: https://doi.org/10.5705/ss.202020.0323
H. Araya and J. Garzón and N. Moreno and F. Plaza (2021). Hermite spatial variations for the solution to the stochastic heat equation. Math. Commun. 26, 253–270.
Contreras-Reyes, J.E., Wiff, R., Soto, J., Donovan, C., Araya, M. (2021). Biphasic growth modelling in elasmobranchs based on asymmetric and heavy-tailed errors. Environmental Biology of Fishes 104 (5), 615–628. DOI: https://doi.org/10.1007/s10641-021-01100-z
Idrovo-Aguirre, B.J., Contreras-Reyes, J.E. (2021). The response of housing construction to a copper price shock in Chile (2009–2020). Economies 9 (3), 98. DOI: https://doi.org/10.3390/economies9030098
Héctor Araya, Johanna Garzón & Tania Roa (2020) Non symmetric Rosenblatt process over a compact, Communications in Statistics – Theory and Methods, DOI: https://doi.org/10.1080/03610926.2020.1734830
Santos-Carvallo M, Barilari F, Pérez-Alvarez MJ, Gutiérrez L, Pavez G, Araya H, Anguita C, Cerda C and Sepúlveda M (2021) Impacts of Whale-Watching on the Short-Term Behavior of Fin Whales (Balaenoptera physalus) in a Marine Protected Area in the Southeastern Pacific. Front. Mar. Sci. 8:623954. doi: https://doi.org/10.3389/fmars.2021.623954
Contreras-Reyes, J.E. (2021). Mutual information matrix based on asymmetric Shannon entropy for nonlinear interactions of time series. Nonlinear Dynamics. DOI: https://doi.org/10.1007/s11071-021-06498-w
Idrovo-Aguirre, B.J., Contreras-Reyes, J.E. (2021). Bayesian monthly index for building activity based on mixed frequencies: the case of Chile. Journal of Economic Studies. DOI: https://doi.org/10.1108/JES-01-2021-0022
Kiseľák, J., Lu, Y., Švihra, J., Szepe, P., Stehlik, M. “SPOCU”: scaled polynomial constant unit activation function. Neural Comput & Applic 33, 3385–3401 (2021). https://doi.org/10.1007/s00521-020-05182-1
Contreras-Reyes, J.E. (2021). Fisher information and uncertainty principle for skew-gaussian random variables. Fluctuation and Noise Letters 20(5), 21500395. DOI: https://doi.org/10.1142/S0219477521500395
Contreras-Reyes, J.E. (2021). Chaotic systems with asymmetric and heavy-tailed noise: application to 3D attractors. Chaos, Solitons & Fractals 145, 110820. DOI: https://doi.org/10.1016/j.chaos.2021.110820
Abid, S.H., Quaez, U.J., Contreras-Reyes, J.E. (2021). An information-theoretic approach for multivariate skew-t distributions and applications. Mathematics 9(2), 146. DOI: https://doi.org/10.3390/math9020146
Héctor Araya, Jorge A. León & Soledad Torres (2021) On local linearization method for stochastic differential equations driven by fractional Brownian motion, Stochastic Analysis and Applications, 39:1, 55-90, https://doi.org/10.1080/07362994.2020.1779746
https://www.tandfonline.com/doi/abs/10.1080/07362994.2020.1779746
Héctor Araya & Ciprian A. Tudor (2021) Asymptotic expansion for the quadratic variations of the solution to the heat equation with additive white noise, Stochastic and Dynamics, Vol. 21, No. 02, 2150010, https://doi.org/10.1142/S0219493721500106
https://www.worldscientific.com/doi/abs/10.1142/S0219493721500106
Ávila, J., Leiva, V., Riquelme, M., Trujillo, L, 2020. The Fay-Herriot model in small area estimation: EM algorithm and application to official data. REVSTAT – Statistical Journal 18(5):613-635.https://revstat.ine.pt/index.php/REVSTAT/article/view/323
Figueroa-Zuñiga, J., Sanhueza, R., Ibacache-Pulgar, G. and Lagos-Alvarez, B. (2020). Trapezoidal Kumaraswamy Distribution. Chilean Journal of Statistics, 11, 163-176. http://soche.cl/chjs/volumes/11/ChJS-11-02-06.pdf
López-Gonzales, J., Calili, R., Leite Coelho da Silva, F., Carbo-Bustinza, N., Ibacache-Pulgar, G. and Castro Souza, R. (2020). Simulation of the Energy Efficiency Auction Prices viaMarkov Chain Monte Carlo Method. Energies, 13, 1-19. https://www.mdpi.com/1996-1073/13/17/4544
Tarasova, E., Drogobuzhskaya, S., Tapia-Pizarro, F., Morev, D.V., Brykov, V.A.,Dovletyarova, E.A., Slukovskaya, M., Navarro-Villarroel, C., Paltseva, A.A.,Neaman, A. (2020). Vermiculite-lizardite industrial wastes promote plant growth in a peat soil affected by a Cu/Ni Smelter: a Case Study at the Kola Peninsula, Russia. Journal of Soil Science and Plant Nutrition 20:1013–1018. https://doi.org/10.1007/s42729-020-00188-z
Prudnikova, E.V., Neaman, A., Terekhova, V.A., Karpukhin, M.M., Vorobeichik, E.L., Smorkalov, I.A., Dovletyarova, E.A., Navarro-Villarroel, C., Ginocchio, R. (2020). A root elongation method for the quality assessment of metal-polluted soils: Whole soil or soil-water extract?. Journal of Soil Science and Plant Nutrition, 20:2294–2303, https://doi.org/10.1007/s42729-020-00295-x
Grigorita G., Neaman, A., Brykova, R., Brykov, V., Morev, D., Ginocchio R., Paltseva, A., Vidal, K., Navarro-Villarroel C., Dovletyarova, E. (2020). Use of Zinc Carbonate spiking to obtain phytotoxicity thresholds comparable to those in field‐collected soils. Environmental Toxicology and Chemistry—Volume 39, Number 9—pp. 1790–1796, wileyonlinelibrary.com).
https://doi.org/10.1002/etc.4809
Stehlík, M, Grilo, L.M., Jordanova, P. Editorial to special issue V WCDANM 2018, Journal of Applied Statistics, 47, https://doi.org/10.1080/02664763.2020.1818489
M. Stehlík, J. Filus, S. Stehlíková, L. Filus, On statistical aspects of advanced stochastic modeling of lava flows of volcano Lonquimay, ICDQM 2020, ISBN 978-86-86355-42-3
Pavlina K. Jordanova and M. Stehlík, Distribution sensitive estimators of the index of regular variation based on ratios of order statistics, AIP Conference Proceedings 2302, 030002 (2020); https://doi.org/10.1063/5.0033940
M. Stehlík, L. Střelec, G. Holzknecht, and J. Kise̞lák, Analysis of ECB consolidated banking data and Covid19-outbreaks: Perspectives for negative interest rates, AIP Conference Proceedings 2302, 030004 (2020); https://doi.org/10.1063/5.0034531
Alejandra Christen, M. Angélica Maulén‐Yañez, Yoselinne Valencia, Eduardo González‐Olivares, Diego F. Rial, Michel Curé. Linear incidence rate: Its influence on the asymptotic behavior of a stochastic epidemic model. https://doi.org/10.1002/mma.6700
Yerel Morales, Marvin Querales, Harvey Rosas, HéctorAllende-Cid, Rodrigo Salas.A Self-Identification Neuro-Fuzzy Inference framework for modeling Rainfall-Runoff in a Chilean watershed. https://doi.org/10.1016/j.jhydrol.2020.125910
Stehlik, M, J. Kiselak, Dinamarca, A. Li, Y. and Ying, Y. On covid19 outbreaks predictions: issues on stability, parameter sensitivity and precision, Stochastic Analysis and Applications, https://doi.org/10.1080/07362994.2020.1802291
J. Kiselak, Y. Lu, J. Svihra, P. Szepe, M. Stehlik (2020) “SPOCU”: scaled polynomial constant unit activation function, Neural Computing and Applications, https://doi.org/10.1007/s00521-020-05182-1
(esta Revista es Q1).
Araya, H., León, J.A. & Torres, S. Numerical Scheme for Stochastic Differential Equations Driven by Fractional Brownian Motion with 1/4<H <1/2.. J Theor Probab 33, 1211–1237 (2020). https://doi.org/10.1007/s10959-019-00902-3
Stehlik et al. (2020), Priority statement and some properties of t-lgHill estimator, Extremes, https://doi.org/10.1007/s10687-020-00375-2
M. Stehlik, J. Kiselak, E. Bukina, Y. Lu, S. Baran, (2020) Fredholm integral relation between compound estimation and prediction (FIRCEP), Stochastic Analysis and Applications, https://doi.org/10.1080/07362994.2019.1696211
P. Mantalos, A. Karagrigoriou, L. Strelec, P. Jordanova, P. Hermann, J. Kiselak, J. Hudak, M. Stehlik, (2020) On improved volatility modelling by fitting skewness in ARCH models, Journal of Applied Statistics, 47:6, 1031-1063, https://doi.org/10.1080/02664763.2019.1671323
L. Salazar, O. Nicolis, F. Ruggeri, J. Kiselak, M. Stehlik (2019) Predicting hourly ozone concentrations using wavelets and ARIMA models, Neural Computing and Applications. 31(8), 4331-4340, https:/doi.org/10.1007/s00521-018-3345-0
Stehlik, M., Mirtha Pari Ruiz, Stehlikova, S. Lu, Y. On equidistant designs, symmetries and their violations in multivariate models, Springer Nature Switzerland AG 2020, Fan and J. Pan (eds.), Contemporary Experimental Design,Multivariate Analysis and Data Mining,https://link.springer.com/chapter/10.1007%2F978-3-030-46161-4_14
Stehlik M., Kiselak, J. and Dusek, J. (2019) On ecosystem dynamics for the conservation of wetlands and forest, Springer, F. Fuders and P. J. Donoso (eds.), Ecological Economic and Socio Ecological Strategies for Forest Conservation, https://doi.org/10.1007/978-
M. Maleki, D. Wraith, M. Mahmoundi and J. Contreras-Reyes. (2020). “Asymmetric heavy-tailed vector auto-regressive processes with application to financial data”. Journal of Statistical Computation and Simulation 90(2), 324-340. doi: https://doi.org/10.1080/00949655.2019.1680675
P. Jordanova and M. Stehlík. (2020). “IPO estimation of heaviness of the distribution beyond regularly varying tails”. Stochastic Analysis and Applications 38(1), 76-96. doi: https://doi.org/10.1080/07362994.2019.1647786
François Bachoc , Moreno Bevilacqua and Daira Velandia. Composite likelihood estimation for a Gaussian process under fixed domain asymptotics (2019).Journal of Multivariate Analysis. https://doi.org/10.1016/j.jmva.2019.104534
J. Palacios-Moreno, C. Rubio, W. Quilhot, M. F. Cavieres, E. de la Peña, N. V. Quiñones, H. Díaz, F. Carrión, C. Henriquez-Roldán and C. R. Weinstein-Oppenheimer. (2019). “Epanorin, a lichen secondary metabolite, inhibits proliferation of MCF-7 breast cancer cells”. Biological Research 52(5), 55. doi: https://doi.org/10.1186/s40659-019-0261-4
P. Jordanova and M. Stehlík. (2019).”Logarithm of ratios of two order statistics and regularly varying tails”. 11th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences (AMiTaNS 2019), Bulgaria, 2019. AIP Conference Proceedings 2164. doi: https://doi.org/10.1063/1.5130791
B. J. Idrovo-Aguirre and J. E. Contreras-Reyes. (2019). “Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015”. Empirical Economics 57(5), 1829-1852. doi: https://doi.org/10.1007/s00181-018-1506-8
O. Nicolis, M. Díaz, S. K. Sahu and J. C. Marin. (2019). “Bayesian spatiotemporal modeling for estimating short‐term exposure to air pollution in Santiago de Chile”. Environmetrics 30(7), e2574. doi: https://doi.org/10.1002/env.2574
M. Bevilacqua and T. Faouzi. (2019). “Estimation and prediction using generalized Cauchy covariance function under fixed domain asymptotics”. Electronic Journal of Statistics, 13(2), 3025-3048. doi: https://doi.org/10.1214/19-EJS1597
L. Salazar, O. Nicolis, F. Ruggeri, J. Kisel’ák and M. Stehlík. “Predicting hourly ozone concentrations using wavelets and ARIMA models”. Neural Computing and Applications, 31(8), 4331–4340. doi: https://doi.org/10.1007/s00521-018-3345-0
R. B. Arellano-Valle, J. E. Contreras-Reyes, F. O. Lopez-Quintero and A. Valdevenito. (2019). “A skew-normal dynamic linear model and bayesian forecasting”. Computational Statistics, 34(3), 1055-1085. doi: https://doi.org/10.1007/s00180-018-0848-1
V. Morales-Oñate and B. Morales-Oñate. (2019).”Una técnica de agrupación robusta para un enfoque big data: CLARABD para tipos de datos mixtos”. Perfiles, 2(12).
M. Tejo, H. Araya, S. Niklitschek-Soto and F. Marmolejo-Ramos. (2019). “Theoretical models of reaction times arising from simple-choice tasks”. Cognitive Neurodynamics, 13(4), 409-416. doi: https://doi.org/10.1007/s11571-019-09532-1
P. Jordanova and M. Stehlík. (2019).”P-thinned gamma process and corresponding random walk”. International Conference of Finite Difference Methods (FDM 2018), Bulgaria, 2018. Finite Difference Methods. Theory and Applications. Lecture Notes in Computer Science, 11386. pp. 297-304. doi: https://doi.org/10.1007/978-3-030-11539-5_33
M. Stehlík, J. P. Maidana, C. Navarro-Villarroel, M. Sepúlveda and D. Oliva. (2019).”On ignorance regions and spatial aspects for south american sea lion (Otary byronia) operational interaction with the artisan gillnet fisher in Chile”. International Conference of Finite Difference Methods (FDM 2018), Bulgaria, 2018. Finite Difference Methods. Theory and Applications. Lecture Notes in Computer Science, 11386. pp. 92-101. doi: https://doi.org/10.1007/978-3-030-11539-5_9
M. Stehlík, L. Núñez-Soza, Z. Fabian, M. Jirina, P. Jordanova, S. Arancibia and J. Kiselak. (2019). “On ecological aspects of dynamics for zero slope regression for water pollution in Chile”. Stochastic Analysis and Applications, 37(4), 574-601. doi: https://doi.org/10.1080/07362994.2019.1592692
D. Travisany, A. Ayala-Raso, A. Di Genova, L. Monsalve, M. Bernales, J. P. Martínez, M. González-Agüero, B. Defilippi, S. Cherian, A. Maass and L. Fuentes. (2019). “RNA-Seq analysis and transcriptome assembly of raspberry fruit (Rubus idaeus ̈Heritage ̈) revealed several candidate genes involved in fruit development and ripening”. Scientia Horticulturae, 254, 26-34. doi: https://doi.org/10.1016/j.scienta.2019.04.018
M. Barasaluce, P. Mondaca, M. Schuhmacher, M. Bravo, S. Sauvé, C. Navarro-Villarroel, E. A. Dovletyarova and A. Neaman. (2019). “Soil and indoor dust as environmental media of human exposure to As, Cd, Cu, and Pb near a copper smelter in central Chile”. Journal of Trace Elements in Medicine and Biology, 54, 156-162. doi: https://doi.org/10.1016/j.jtemb.2019.04.006
M. Bernales, L. Monsalve, A. Ayala-Raso, M. Valdenegro, J. P. Martínez, D. Traviani, B. Defilippi, M. González-Agüero, S. Cherian and L. Fuentes. (2019). “Expression of two indole-3-acetic acid (IAA)-amido synthetases (GH3) genes during fruit development and ripening of raspberry (Rubus idaeus Heritage)”. Scientia Horticulturae, 246, 168-175. doi: https://doi.org/10.1016/j.scienta.2018.09.077
M. Bevilacqua, T. Faouzi, R. Furrer and E. Porcu. (2019). “Estimation and prediction using generalized wendland covariance function under fixed domain asymptotics”. Annals of Statistics, 47(2), 828–856. doi: https://doi.org/10.1214/17-AOS1652
A. Hoseinzadeh, M. Maleki, Z. Khodadadi and J. E. Contreras-Reyes. (2019). “The Skew-Reflected-Gompertz distribution for analyzing symmetric and asymmetric data”. Journal of Computational and Applied Mathematics, 349, 132-141. doi:: https://doi.org/10.1016/j.cam.2018.09.011
L. Núñez-Soza, P. Jordanova, O. Nicolis, L.Střelec and M. Stehlík. (2019). “Small sample robust approach to outliers and correlation of atmospheric pollution and health effects in Santiago de Chile”. Chemometrics and Intelligent Laboratory Systems. 185, 73-84. doi: https://doi.org/10.1016/j.chemolab.2018.12.010
J. Cavieres and O. Nicolis. (2018). “Using a spatio-temporal Bayesian approach to estimate the relative abundance index of yellow squat lobster (Cervimunida johni) off Chile”. Fisheries Research. 28, 97-104. doi: https://doi.org/10.1016/j.fishres.2018.07.002
P. Jordanova, Z. Sadovský and M. Stehlík. (2017). “Modelling of snow exceedances”. International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2016), Greece, 2016, AIP Conference Proceedings, 1863. doi: https://doi.org/10.1063/1.4992285
M. Stehlík, J. Kisełák, G. Holzknecht and F. Fuders. (2017). “On flexible modeling of generalized interest rate”. International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences (AMiTaNS 2017), Bulgaria, 2017, AIP Conference Proceedings, 1895. doi: https://doi.org/10.1063/1.5007363
P. Jordanova, M. P. Petkova and M. Stehlík. (2017). “Inverse log-gamma-g processes”. International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences (AMiTaNS 2017), Bulgaria, 2017, AIP Conference Proceedings, 1895. doi: https://doi.org/10.1063/1.5007362
M. Stehlík and J. Kiseľák. (2017). “On stochastic representation of blow-ups for distributed parameter systems”. International Conference on Numerical Analysis and Its applications (NAA 2016), Bulgaria, 2016. Numerical Analysis and Its Applications. Lecture Notes in Computer Science, 10187. pp. 132-140. doi: https://doi.org/10.1007/978-3-319-57099-0_12
P. Jordanova, M. P. Petkova and M. Stehlík. (2017). “Compound log-series distribution with negative multinomial summands”. International Conference on Numerical Analysis and Its Applications (NAA 2016), Bulgaria, 2016. Numerical Analysis and Its Applications. Lecture Notes in Computer Science, 10187. pp. 383-390. doi: https://doi.org/10.1007/978-3-319-57099-0_42
V. Morales-Oñate and B. Morales-Oñate. (2017). “Regresión lineal bajo diseños muestrales complejos: un enfoque aplicado”. Analitika, 14(2), 103-124.
R. Potocky, C. Navarro-Villarroel, M. Sepúlveda M. and M. Stehlík. (2017). “Random elements on lattices: Review and statistical applications,”. International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2016), Greece, 2016. AIP Conference Proceedings, 1863(1). doi: https://doi.org/10.1063/1.4992283
D. Nava, F. De Bastiani, M. Uribe-Opazo, O. Nicolis and M. Galea. (2017). “Local Influence for Spatially Correlated Binomial Data: An Application to the Spodoptera frugiperda Infestation”. Journal of Agricultural, Biological and Environmental Statistics, 22(4), 540-561. doi: https://doi.org/10.1007/s13253-017-0306-5
A. R. Francis, M. Stehlík and H. P. Wynn. (2017). “Building exact confidence nets”. Bernulli, 23(4B), 3145-3165. doi: https://doi.org/10.3150/16-BEJ839
R. B. Arellano-Valle, J. E. Contreras-Reyes and M. Stehlík. (2017). “Generalized Skew-Normal Negentropy and Its Application to Fish Condition Factor Time Series”. Entropy, 19(10), 528. doi: https://doi.org/10.3390/e19100528
J. Kiseľák, P. Hermann and M. Stehlík. (2017). “Negative interest rates: why and how?”. Mathematica Slovaca, 67(5), 1165-1178. doi: https://doi.org/10.1515/ms-2017-0040
M.Stehlík, P. Hermann, S.Torres, J. Kiseľák and A.Rivera. (2017). “On dynamics underlying variance of mass balance estimation in Chilean glaciers”. Ecological Complexity, 31, 149-164. doi: https://doi.org/10.1016/j.ecocom.2017.06.008
O. Nicolis, F. Kiselak-Porro and M. Stehlík. (2017). “Multi-fractal cancer risk assessment”. Stochastic Analysis and Applications, 35(2), 237-256. doi: https://doi.org/10.1080/07362994.2016.1238766
F. O. Lopez-Quintero, J. E. Contreras-Reyes and R. Wiff. (2017). “Incorporating uncertainty into a length-based estimator of natural mortality in fish populations”. Fishery Bulletin, 115(3), 355-364. doi: https://doi.org/10.7755/FB.115.3.6
M. Stehlík, Ch.Helperstorfer, P.Hermann, J.Šupina, L.M. Grilo, J.P.Maidana, F.Fuders and S. tehlíková. (2017). “Finantial and risk modelling with semicontinuous covariances”. Information Sciences, 394-395, 246-272. doi: https://doi.org/10.1016/j.ins.2017.02.002
I. Mozos, J. P. Maidana, D. Stoian and M. Stehlik. (2017). “Gender Differences of Arterial Stiffness and Arterial Age in Smokers”. International Journal of Environmental Research and Public Health, 14, 565. doi: https://doi.org/10.3390/ijerph14060565
W. D. Richter, L. Střelec, H. Ahmadinezhad and M. Stehlík. (2017). “Geometric aspects of robust testing for normality and sphericity”. Stochastic Anaysis and Applications, 35(3). 511-532. doi: https://doi.org/10.1080/07362994.2016.1273785
M.Stehlík, P.Aguirre, S. Girardd. Jordanova, J. Kiseľák, S. Torres, Z.Sadovský and A.Rivera. (2017). “On ecosystems dynamics”. Ecological Complexity, 29, 10-29. doi: https://doi.org/10.1016/j.ecocom.2016.11.002
P. Jordanova, Y. Nefedova and M.Stehlík. (2017). “Risk process approximation woth mixing”. Applied Mathematical Modelling, 41, 284-298. doi: https://doi.org/10.1016/j.apm.2016.08.028
M. Stehlík, J. Kiseľák, R. Potocký and P. Jordanova. (2017). “Generalized interest rate dynamics and its impacts on finance and pensions”. Stochastic Analysis and Applications, 35(1). 178-190. doi: https://doi.org/10.1080/07362994.2016.1224975
F. Cuevas, E. Porcu and M. Bevilacqua. (2017). “Contours and Dimples for the Gneiting class of Space-Time Covariance Functions”. Biometrika, 104(4), 995-1001. doi: https://doi.org/10.1093/biomet/asx048
E. Porcu, V. Zastavnyi and M. Bevilacqua. (2017). “Buhmann Covariance Functions, their Compact Supports, and their Smoothness”. Dolomites Research Notes on Approximation, 10(1), 33-42. doi: https://doi.org/10.14658/pupj-drna-2017-1-5
A. Alegrıa, S. Caro, M. Bevilacqua, E. Porcu and J. Clarke. (2017). “Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere”. Spatial Statistics, 22(2), 388-402. doi: https://doi.org/10.1016/j.spasta.2017.07.009
D. Velandia, F. Bachoc, M. Bevilacqua, X. Gendre and J. M. Loubes. (2017). “Maximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics”. Electronic Journal of Statistics, 11(2), 2978-3007. doi: https://doi.org/10.1214/17-EJS1298
K. C. Cuadros, K. G. Padilha, M. C. Toffoletto, C. Henriquez-Roldán and M. A. J. Canales. (2017). “Patient Safety Incidents and Nursing Workload”. Revista Latino-Americana de Enfermagem, 25, e2841. doi: http://dx.doi.org/10.1590/1518-8345.1280.2841
P. Jordanova, M. P. Petkova and M. Stehlík. (2016). “Compound negative binomial distribution with negative multinomial summands”. International Conference on Applications of Mathematics in Engineering and Economics (AMEE 2016), Bulgaria, 2016, AIP Conference Proceedings, 1789. doi: https://doi.org/10.1063/1.4968501
M. Stehlík, S. Stehlíková and S. Torres. (2016). “Understanding water extremes with caution”. International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2015), Greece, 2015, AIP Conference Proceedings, 1738. doi: https://doi.org/10.1063/1.4951814
S. Ramos-Avasola, C. Kartulovic, C. Gamboa, J. Gamarra and M. Catalán. (2016). “¿Son reproducibles las mediciones dosimétricas a bajas dosis en cardiologóa intervencionista?”. Revista Chilena de radiología, 22(2), 70-75. doi: https://doi.org/10.1016/j.rchira.2016.06.003
L. Fuentes, M. Valdenegro, M. G, Gómez ,A. Ayala-Raso, E. Quiroga, J. P. Martínez, R. Vinet, E. Caballero, C. R. Figueroa. (2016). “Characterization of fruit development and potential health benefits of arrayan (Luma apiculata), a native berry of South America”. Food Chemistry, 196, 1239-1247. doi: https://doi.org/10.1016/j.foodchem.2015.10.003
P. Jordanova, Z. Fabián, P. Hermann, L. Střelec, A. Rivera, S. Girard, S. Torres and M. Stehlík. (2016). “Weak properties and robustness of t-Hill estimators”. Extremes, 19(4), 591-626. doi: https://doi.org/10.1007/s10687-016-0256-2
J. Paseka, S. A. Solovyov and M. Stehlík. (2016). “On a topological universe of L-bornological spaces”. Soft Computing, 20(7), 2503-2512. doi: https://doi.org/10.1007/s00500-015-1905-0
S. Ramos-Avasola, N. Diaz, R. Roldan, J. Gamarra and M. Catalan. (2016). “Radiation protection provided by tungsten bismuth caps during interventional cardiology”.Revista Médica de Chile, 144(7), 837-843. doi: https://doi.org/10.4067/S0034-98872016000700003
M. Stehlík, P. Hermann and O. Nicolis. (2016). “Fractal based cancer modelling”. REVSTAT – Statistical Journal, 14 (2), 139-155.
P. Jordanova and M. Stehlík. (2016).”Mixed Poisson process with Pareto mixing variable and its risk applications”. Lithuanian Mathematical Journal, 56(2), 189–206. doi: https://doi.org/10.1007/s10986-016-9313-4
M. Stehlík. (2016). “On convergence of topological aggregation functions”. Fuzzy Sets and Systems, 287, 48-56. doi: https://doi.org/10.1016/j.fss.2014.11.022
M. Stehlík, J. Dusek and Kiseľák. (2016). “Missing chaos in global climate change data interpreting?”. Ecological Complexity, 25, 53-59. doi: https://doi.org/10.1016/j.ecocom.2015.12.003
M. Bevilacqua, A. Alegria, D. Velandia and E. Porcu. (2016). “Composite likelihood inference for multivariate Gaussian random fields”. Journal of Agricultural Biological and Environmental Statistics, 21(3), 448-469. doi: https://doi.org/10.1007/s13253-016-0256-3
A. Alegria, M. Bevilacqua and E. Porcu. (2016). “Likelihood-based inference for multivariate space-time wrapped-Gaussian fields”. Journal of Statistical Computation and Simulation, 86(13), 2583-2597. doi: https://doi.org/10.1080/00949655.2016.1162309
M. Bevilacqua, A. Fassò, C. Gaetan, E. Porcu and D. Velandia. (2016). “Covariance tapering for multivariate Gaussian random fields estimation”. Statistical Methods and Application, 25(1), 21-37. doi: https://doi.org/10.1007/s10260-015-0338-3
S. Liu, V. Leiva, T. Ma and A Welsh. (2016). “Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions”. Statistical Methods and Applications, 25(2), 227-249. doi: https://doi.org/10.1007/s10260-015-0329-4
V. Leiva, S. Lui, L. Shi and F. Cysneiros. (2016). “Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics”. Journal of Applied Statistics, 43(4), 627-642. doi: https://doi.org/10.1080/02664763.2015.1072140
V. Leiva, M. Ferreira, M. I. Gomes and C. Lillo. (2016). “Extreme value Birnbaum-Saunders regression models applied to environmental data”. Stochastic Environmental Research and Risk Assessment, 30(3), 1045-1058. doi: https://doi.org/10.1007/s00477-015-1069-6
V. Leiva, M. Santos-Neto, F. Cysneiros and M. Barros. (2016). “A methodology for stochastic inventory models based on a zero-adjusted Birnbaum-Saunders distribution”. Applied Stochastic Models in Business and Industry, 31, 74-89. doi: https://doi.org/10.1002/asmb.2124
M. Bevilacqua, R. Vallejos and D. Velandia. (2015). “Assessing the significance of the correlation between the components of a bivariate Gaussian random field”. Environmetrics, 26(8), 545-556. doi: https://doi.org/10.1002/env.2367
E. Porcu, M. Bevilacqua and M. Genton. (2015). “Spatio-Temporal Covariance and Cross-Covariance Functions of the Great Circle Distance on a Sphere”. Journal of the American Statistical Association, 111(514), 888-898. doi: https://doi.org/10.1080/01621459.2015.1072541
M. Bevilacqua, A. S. Hering and E. Porcu. (2015). “On the flexibility of multivariate covariance models: Comment on the Paper by Genton and Kleiber”. Statistical Science, 30(2), 167–169. doi: https://doi.org/10.1214/15-STS516
S. Padoan and M. Bevilacqua. (2015). “Analysis of Random Fields Using CompRandFld”. Journal of the Statistical Software, 63(9), 1-27. doi: http://hdl.handle.net/10.18637/jss.v063.i09
M. Bevilacqua and C. Gaetan. (2015). “Comparing composite likelihood methods based on pairs for spatial Gaussian random fields”. Statistics and Computing, 25(5), 877-892. doi: https://doi.org/10.1007/s11222-014-9460-6
M. Bevilacqua, F. Crudu and E. Porcu. (2015). “Combining Euclidean and composite likelihood for binary spatial data estimation”. Stochastic Environmental Research and Risk Assessment, 29(2), 335-346. doi: https://doi.org/10.1007/s00477-014-0938-8
J. D. Daley, E. Porcu and M. Bevilacqua. (2015). “Classes of compactly supported covariance functions for multivariate random fields”. Stochastic Environmental Research and Risk Assessment. 29(4), 1249-1263. doi: https://doi.org/10.1007/s00477-014-0996-y
O. Nicolis and J. Mateu. (2015). “2D Anisotropic Wavelet Entropy with an Application to Earthquakes in Chile”. Entropy, 17(6), 4155-4172. doi: https://doi.org/10.3390/e17064155
O. Nicolis and J. Mateu. (2015). “Discussion of the paper Analysis of Spatio-Temporal Mobile Phone Data: a Case Study in the Metropolitan Area of Milan”. Statistical Methods and Applications, 24(2), 315-319. doi: https://doi.org/10.1007/s10260-015-0311-1
P. Hermann, T. Mrkvicka, T. Mattfeldt, M. Minrov, K. Helisov, O. Nicolis, F. Wartner M. Stehlík. (2015). “Fractal and Stochastic Geometry Inference for Breast Cancer: Case Study with Random Fractals Models and Quermass-Interaction Process”. Statistics in Medicine, 34 (18), 2636–2661. doi: https://doi.org/10.1002/sim.6497
O. Nicolis, M. Chiodi and G. Adelfio. (2015). “Windowed ETAS models with application to the Chilean seismic catalogs”. Spatial Statistics, 14 (B), 151-165. doi: https://doi.org/10.1016/j.spasta.2015.05.006
J. Mateu and O. Nicolis. (2015). “Multiresolution analysis of linearly-oriented spatial point patterns”. Journal of Statistical Computation and Simulation, 85 (3), 621-637. doi: https://doi.org/10.1080/00949655.2013.838565
J. Duran, M. P. Sanchez, M. Mola, V. Götzens, J. Carballo, E. M. Pelegrina, M. Petit, O. Abdul-Jawad, I. Otaegui, B. G. del Blanco, D. García-Dorado, J. Reig, A. Cordero and J. M. de Anta. (2015). “Genetic association study of coronary collateral circulation in patients with coronary artery disease using 22 single nucleotide polymorphisms corresponding to 10 genes involved in postischemic neovascularization”. BCM Cardiobascular Disorders, 15, 37. doi: https://doi.org/10.1186/s12872-015-0027-z
B. G. Cobo, L. Rodriguez, M. Catalan, M. Lutz. (2015). “Sodium content of meals provided by the National Public Schools Feeding Program and its realtionship with nutritional status and blood pressure in children from first grade, Quillota, Chile”. Revista Chilena de Nutrición, 42(2), 114-120. doi: https://doi.org/10.4067/S0717-75182015000200001
J. Ocana, M. P. Sanchez and J. L. Carrasco. (2015). “Carryover negligibility and relevance in bioequivalence studies”. 15(5), 400-408. doi: https://doi.org/10.1002/pst.1699
E. Deniz-Howe and O. Nicolis. (2015). “Genetic Algorithm in the Wavelet Domain for Large p Small n Regression”. Communications in Statistics – Theory and Methods, 44(5), 1144-1157. doi: https://doi.org/10.1080/03610918.2013.809101
V. Leiva, C. Marchant, F. Ruggeri and H. Saulo. (2015). “A criterion for environmental assessment using Birnbaum-Saunders attribute control charts”. Environmetrics, 26(7), 463-476. doi: https://doi.org/10.1002/env.2349
L. Sanchez, V. Leiva, F. J. Caro-Lopera and F. Cysneiros. (2015). “On matrix-variate Birnbaum-Saunders distributions and their estimation and application”. Brazilian Journal of Probability and Statistics, 29(4), 790-812. doi: https://doi.org/10.1214/14-BJPS247
R. Fierro, V. Leiva and J. Moller. (2015). “The hawkes process with different exciting functions and its asymptotic behavior”. Journal of Applied Probability, 52, 37-54. doi: https://doi.org/10.1239/jap/1429282605
G. Guillot, R. Schilling, E. Porcu and M. Bevilacqua. (2014). “Valid covariance models for the analysis of geographical genetic variation”. Methods in Ecology and Evolution, 5(4), 329-335. doi: https://doi.org/10.1111/2041-210X.12167
G. Ibacache-Pulgar, G. A. Paula and M. Galea. (2014). “On influence diagnostics in elliptical multivariate regression models with equicorrelated random errors”. Statistical Methodology, 16, 14-31. doi: https://doi.org/10.1016/j.stamet.2013.06.001
V. Leiva, H. Saulo, J. Leao and C. Marchant. (2014) .”A family of autoregressive conditional duration models applied to financial data”. Computational Statistics and Data Analysis, 79, 175-191. doi: https://doi.org/10.1016/j.csda.2014.05.016
E. Frutos, M. P. Galindo and V. Leiva. (2014). “An interactive biplot implementation in R for modeling genotype-by-environment interaction”. Stochastic Environmental Research and Risk Assessment, 28(7), 1629-1641. doi: https://doi.org/10.1007/s00477-013-0821-z
V. Leiva, C. Marchant, H. Saulo, M. Aslam and F. Rojas. (2014). “Capability indices for Birnbaum-Saunders processes applied to electronic and food industries”. Journal of Applied Statistics, 41(9), 1881-1902. doi: https://doi.org/10.1080/02664763.2014.897690
M. Barros, V. Leiva, R. Ospina and A. Tsuyuguchi. (2014). “Goodness-of-Fit Tests for the Birnbaum-Saunders Distribution With Censored Reliability Data”. IEEE Transactions on Reliability, 63(2), 543-554. doi: https://doi.org/10.1109/TR.2014.2313707
V. Leiva, E. Rojas, M. Galea and A. Sanhueza. (2014). “Diagnostics in Birnbaum-Saunders accelerated life models with an application to fatigue data”. Applied Stochastic Models in Business and Industry, 30(2), 115-131. doi: https://doi.org/10.1002/asmb.1944
V. Leiva, M. Santos-Neto, F. Cysneiros and M. Barros. (2014). “Birnbaum–Saunders statistical modelling: a new approach”. Statistical Modelling, 14(1), 21-48. doi: https://doi.org/10.1177/1471082X13494532
N. Remenyi, O. Nicolis, G. Nason and B. Vidakovic. (2014). “Image Denoising with 2-D Scale- Mixing Complex Wavelet Transforms”. IEEE TRANSACTIONS ON IMAGE PROCESSING, 23(12), 5165 – 5174. doi: https://doi.org/10.1109/TIP.2014.2362058
M. Santon-Neto, J. A. Cysneiros, V. Leiva and M. Barros. (2014). “A reparameterized Birnbaum-Saunders distribution and its moments, estimation and applications”. REVSTAT-Statistical Journal, 12(3), 247-272.
F. O. Lopez-Quintero and E. Porcu. (2014). “Extensions of object oriented data analysis”. Biometrical Journal, 56(5), 764-765. doi: https://doi.org/10.1002/bimj.201300181
E. Porcu, D. J. Daley, M. Buhmann and M. Bevilacqua. (2013). “Radial basis functions with compact support for multivariate geostatistics”. Stochastic Environmental Research and Risk Assessment, 27(4), 909-922. doi: https://doi.org/10.1007/s00477-012-0656-z
E. Porcu and R. L. Schilling. (2013). “From Scholenberg to Pick Nevanlinna: Towards a complete picture of the variogram class”. Bernoulli, 19(5B), 2768-2768. doi: https://doi.org/10.3150/12-BEJ465
G. Ibacache-Pular, G. A. Paula, F. Cysneiros. (2013). “Semiparametric additive models under symmetric distributions”. Test, 22(1), 103-121. doi: https://doi.org/10.1007/s11749-012-0309-z.
F. Cuevas, E. Porcu and R. Vallejos. (2013). “Study of spatial relationships between two sets of variables: a nonparametric approach”. Journal of Nonparametrics Statistics, 25(3), 695-714. doi: https://doi.org/10.1080/10485252.2013.797091.
M. Amos-Salas, J. Lopez-Hidalgo, E. Porcu. (203). “Optimal designs for some stochastic processes whose covariance is a function of the mean”. Test, 22(1), 159-181. doi: https://doi.org/10.1007/s11749-012-0311-5.
F. Villanca, M. Rodriquez-Motta and L. Victor. (2013). “On a variante stabilizing models and its applications to genomic data”. Journal of Applied Statistics, 40(11), 2354-2371. doi: https://doi.org/10.1080/02664763.2013.811480.
H. Saulo, V. Leiva, F. A. Ziegelmann and C. Marchant. (2013). “A nonparametric method for estimating asymmetric densities based on skewed Birnbaum-Saunders distributions applied to environmental data”. Stochastic and Environmental Research and Risk Assessment, 27(6), 1479-1491. doi: https://doi.org/10.1007/s00477-012-0684-8.
C. Marchant, K. Bertine, V. Leiva and H. Sulo. (2013). “Generalized Birnbaum-Saunders kernel density estimators and an analysis of finantial data”. Computational Statistics and Data Analysis, 63, 1-15. doi: https://doi.org/10.1016/j.csda.2013.01.013.
R. Fierro, V. Leiva, F. Ruggeri and A. Sanhueza. (2013). “On a Birnbaum-Saunders distribution arasing from non-homogeneous Poisson process”. Statistics and Probability Letters, 83(4), 1233-1339. doi: https://doi.org/10.1016/j.spl.2012.12.018.
D. M. Kelmansky, E. J. Martinez and V. Leiva. (2013). “A new stabilizing transformation for gene expression data analysis”. Statistical Application in Genetics and Molecular Biology, 12(6), 653-666. doi: https://doi.org/10.1515/sagmb-2012-0030.
Contreras-Reyes, J.E., Palma, W. (2013). Statistical analysis of autoregressive fractionally integrated moving average models in R. Computational Statistics 28(5), 2309–2331. DOI: https://doi.org/10.1007/s00180-013-0408-7
Contreras-Reyes, J.E. (2013). Nonparametric Assessment of Aftershock Clusters of the Maule Earthquake
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Contreras-Reyes, J.E., Arellano-Valle, R.B. (2012). Kullback–Leibler divergence measure for multivariate skew-normal distributions. Entropy 14(9), 1606–1626. DOI:https://doi.org/10.3390/e14091606
C. Meza, F. Osorio and R. de la Cruz. (2012). “Estimation in nonlinear mixed-effects models using heavy-tailed distributions”. Statistics and Computing, 22(1), 121-139. doi:https://doi.org/10.1007/s11222-010-9212-1
V. Leiva, M. G. Ponce, C. Marchant and O. Bustos. (2012). “Fatigue statistical distributions useful for modeling diameter and mortality trees”. Revista Colombiana de Estadística, 35(3), 349-370.
C. Azevedo, V. Leiva, E. Athayde and N. Balakrishnan. (2012). “Shape and change point analyses of the Birnbaum-Saunders-t hazard rate and associated estimation”. Computional Statistics and Data Analysis, 56(12), 3887-3897. doi:https://doi.org/10.1016/j.csda.2012.05.007
M. Catalan, M. P. Galindo, J. Martin and V. Leiva. (2012). “Integration methods of odds ratio based on meta-analysis using fixed and random effects models”. Revista Colombiana de Estadística, 35(2), 205-222.
M. Ferreira, M. I. Gomes and V. Leiva. (2012). “On a extreme value version of the Birnbaum-Saunders distribution”. REVSTAT – Statistical Journal, 10(2), 181 +.
F. J. Caro-Lopera, V. Leiva and N. Balakrishnan. (2012). “Connections between the Hadamard and matrix products with an application to matrix-variate Birnbaum-Saunders distributions”. Journal of Multivariate Analysis, 104(1), 126-139. doi:https://doi.org/10.1016/j.jmva.2011.07.004.
E. Athayde, C. Azevedo, V. Leiva and A. Sanhueza. (2012). “About Birnbaum-Saunders distribution based on the Johnson system”. Communications in Statistcs-Theory and Methods, 41(11), 2061-2079. doi:https://doi.org/10.1080/03610926.2010.551454.
M. Santos-Neto, F. Cysneiros, V. Leiva and S. E. Ahmed. (2012). “On new parametrizations of the Birnbaum-Saunders distribution”. Pakistan Journal of Statistics, 28(1), 1-26.
G. A. Paula, V. Leiva, M. Barros and S. Z. Liu. (2012). “Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance”. Applied Stochastic Models in Bussiness and Industry, 28(1), 16-34. doi:https://doi.org/10.1002/asmb.887