G. Martínez-Flórez, M. Pacheco-López, Roger Tovar-Falón
{"title":"Likelihood-Based Inference for the Asymmetric Exponentiated Bimodal Normal Model","authors":"G. Martínez-Flórez, M. Pacheco-López, Roger Tovar-Falón","doi":"10.15446/rce.v45n2.95530","DOIUrl":"https://doi.org/10.15446/rce.v45n2.95530","url":null,"abstract":"Asymmetric probability distributions have been widely studied by various authors in recent decades, who have introduced new families of flexible distributions in terms of skewness and kurtosis than the classical distributions known in statistical theory. Most of the new distributions fit unimodal data, others fit bimodal data, however, in the bimodal, singularity problems have been found in their information matrices in most of the proposals presented. In contrast, in this paper an extension of the family of alpha-power distributions was developed, which has a non-singular information matrix, based on the bimodal-normal and bimodal elliptic-skew-normal probability distributions. These new extensions model asymmetric bimodal data commonly found in various areas of scientific interest. The properties of these new probabilistic distributions were also studied in detail and the respective statistical inference process was carried out to estimate the parameters of these new models. The stochastic convergence for the vector of maximum likelihood estimators could be found due to the non-singularity of the expected information matrix in the corresponding support.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41715087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Forecasting with Multivariate Threshold Autoregressive Models","authors":"Sergio Calderon, Fabio H. Nieto","doi":"10.15446/RCE.V44N2.91356","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.91356","url":null,"abstract":"\u0000 \u0000 \u0000An important stage in the analysis of time series is the forecasting. How- ever, the forecasting in non-linear time series models is not straightforward as in linear time series models because an exact analytical of the conditional expectation is not easy to obtain. Therefore, a strategy of forecasting with multivariate threshold autoregressive(MTAR) models is proposed via predictive distributions through Bayesian approach. This strategy gives us the forecast for the response and exogenous vectors. The coverage percentages of the forecast intervals and the variability of the predictive distributions are analysed in this work. An application to Hydrology is presented. \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 \u0000","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42303515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Results on the Fractional Cumulative Residual Entropy of Coherent Systems","authors":"S. Tahmasebi, Reza Mohammadi","doi":"10.15446/RCE.V44N2.86562","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.86562","url":null,"abstract":"Recently, Xiong et al. (2019) introduced an alternative measure of uncertainty known as the fractional cumulative residual entropy (FCRE). In this paper, first, we study some general properties of FCRE and its dynamic version. We also consider a version of fractional cumulative paired entropy for a random lifetime. Then we apply the FCRE measure for the coherent system lifetimes with identically distributed components.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41976029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian Estimation of Morgenstern Type Bivariate Rayleigh Distribution Using Some Types of Ranked Set Sampling","authors":"Mehdi Basikhasteh, Fazlollah Lak, S. Tahmasebi","doi":"10.15446/RCE.V44N2.87825","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.87825","url":null,"abstract":"In this paper we consider Bayesian estimation based on bivariate ranked set sample, in which units are ranked based on measurements made on an easily and exactly measurable auxiliary variable X which is correlated with the study variable Y. We obtain Bayes estimator for the scale parameter of the study variate Y, when (X, Y ) follows a Morgenstern type bivariate Rayleigh distribution. The Bayes estimators are considered based on bivari-ate ranked set sampling, extreme ranked set sampling and maximum ranked set sampling with unequal sample. The accuracy of estimation methods in this paper is illustrated using simulation study. Finally, a real data set is analyzed.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44807519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter O. Peter, B. Oluyede, H. Bindele, Nkumbuludzi Ndwapi, Onkabetse V Mabikwa
{"title":"The Gamma Odd Burr III-G Family of Distributions: Model, Properties and Applications","authors":"Peter O. Peter, B. Oluyede, H. Bindele, Nkumbuludzi Ndwapi, Onkabetse V Mabikwa","doi":"10.15446/RCE.V44N2.89320","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.89320","url":null,"abstract":"A new family of distributions called Ristic-Balakhrishnan Odd Burr III-G (RBOB III-G) distribution is proposed. We obtain some mathematical and statistical properties of this distribution such as hazard and reverse hazardfunctions, quantile function, moments and generating functions, conditional moments, Rényi entropy, order statistics, stochastic ordering and probability weighted moments. The model parameters are estimated using maximum likelihood estimation technique. Finally, the usefulness of this family of distributions is demonstrated via simulation experiments.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41557769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Diniz, R. Pires, Carolina C. M. Paraiba, P. Ferreira
{"title":"Influence Diagnostics for Correlated Binomial Regression Models: An Application to a Data Set on High-Cost Health Services Occurrence","authors":"C. Diniz, R. Pires, Carolina C. M. Paraiba, P. Ferreira","doi":"10.15446/RCE.V44N2.85606","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.85606","url":null,"abstract":"This paper considers a frequentist perspective to deal with the class of correlated binomial regression models (Pires & Diniz, 2012), thus providing a new approach to analyze correlated binary response variables. Model parameters are estimated by direct maximization of the log-likelihood function. We also consider a diagnostic analysis under the correlated binomial regression model setup, which is performed considering residuals based on predictive values and deviance residuals (Cook & Weisberg, 1982) to check for model assumptions, and global in˛uence measure based on case-deletion (Cook, 1977) to detect in˛uential observations. Moreover, a sensitivity analysis is carried out to detect possible in˛uential observations that could a˙ect the inferential results. This is done using local in˛uence metrics (Cook, 1986) with case-weight, response, and covariate perturbation schemes. A simulation study is conducted to assess the frequentist properties of model parameter estimates and check the performance of the considered diagnostic metrics under the correlated binomial regression model. A data set on high-cost claims made to a private health care provider in Brazil is analyzed to illustrate the proposed methodology.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41624742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exponentiality Test Based on Progressively Type-II Censored Data Via Extension of Cumulative Tsallis Divergence","authors":"V. Ahrari, A. Habibirad","doi":"10.15446/RCE.V44N2.89797","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.89797","url":null,"abstract":"In this article, first new divergences are defined by using Tsallis divergence and a measure of discrepancy between equilibriums associated with two distributions is proposed. Then utilizing the progressively Type-II censored sample, we construct goodness of fit tests for exponentiality based on the estimation of proposed divergences. To investigate the performance of the mentioned tests, Monte Carlo simulations are performed. In order to study the power, the alternatives are considered according to the failure rate function. The powers of the proposed tests are then compared with other existing tests. As regards the last step of the study, in order to explain the use of the proposed tests, three examples are presented.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jinxiang Hu, Lauren Clark, Peng Shi, Vincent S Staggs, Christine Daley, Byron Gajewski
{"title":"Bayesian Hierarchical Factor Analysis for Efficient Estimation across Race/Ethnicity.","authors":"Jinxiang Hu, Lauren Clark, Peng Shi, Vincent S Staggs, Christine Daley, Byron Gajewski","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for differential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show that fitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.</p>","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"44 2","pages":"313-329"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356675/pdf/nihms-1695908.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39311592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jinxiang Hu, Lauren Clark, Peng Shi, V. Staggs, Christine M. Daley, B. Gajewski
{"title":"Bayesian Hierarchical Factor Analysis for Efficient Estimation across Race/Ethnicity.","authors":"Jinxiang Hu, Lauren Clark, Peng Shi, V. Staggs, Christine M. Daley, B. Gajewski","doi":"10.15446/RCE.V44N2.87690","DOIUrl":"https://doi.org/10.15446/RCE.V44N2.87690","url":null,"abstract":"Patient reported outcomes are gaining more attention in patient-centered health outcomes research and quality of life studies as important indicators of clinical outcomes, especially for patients with chronic diseases. Factor analysis is ideal for measuring patient reported outcomes. If there is heterogeneity in the patient population and when sample size is small, differential item functioning and convergence issues are challenges for applying factor models. Bayesian hierarchical factor analysis can assess health disparity by assessing for differential item functioning, while avoiding convergence problems. We conducted a simulation study and used an empirical example with American Indian minorities to show that fitting a Bayesian hierarchical factor model is an optimal solution regardless of heterogeneity of population and sample size.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":"313-329"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79092332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}