{"title":"Editorial","authors":"L. López Kleine, Ramón Giraldo Henao","doi":"10.15446/rce.v42n2.81124","DOIUrl":"https://doi.org/10.15446/rce.v42n2.81124","url":null,"abstract":"Dear readers, We welcome you to the second issue of the year 2019. This time we have twoimportant announcements to make.First, the creation of a new section in our journal. We have decided to create anew section of “Applied Statistics”. The section of applied statistics will cover thewhole range of interdisciplinary fields, for example applications of statistical meth-ods as well as data analytics in agriculture, genetics, industry, medicine, economyand physical sciences. In this section, original or innovative applications that makea novel contribution to statistics by adapting or developing methodology, or byapplying it for the first time in a field will be consideredSecond, the citation index of RCE has been growing steadily. Now we haveachieved to pass to Q2 with a Scimago index of 0.94.We hope you enjoy this issue and invite you to continue reading and submittingyour work to Colombian Journal of Statistics.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/rce.v42n2.81124","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47365567","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":"A New Extended Mixture Skew Normal Distribution, With Applications","authors":"H. M. Barakat, A. W. Aboutahoun, N. El-kadar","doi":"10.15446/RCE.V42N2.70087","DOIUrl":"https://doi.org/10.15446/RCE.V42N2.70087","url":null,"abstract":"One of the most important property of the mixture normal distributions-model is its flexibility to accommodate various types of distribution functions (df's). We show that the mixture of the skew normal distribution and its reverse, after adding a location parameter to the skew normal distribution, and adding the same location parameter with different sign to its reverse is a family of df's that contains all the possible types of df's. Besides, it has a very remarkable wide range of the indices of skewness and kurtosis. Computational techniques using EM-type algorithms are employed for iteratively computing maximum likelihood estimates of the model parameters. Moreover, an application with a body mass index real data set is presented.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N2.70087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47033472","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}
E. Coelho-Barros, J. Achcar, E. Martinez, N. Davarzani, H. Grabsch
{"title":"Bayesian Inference For The Segmented Weibull Distribution","authors":"E. Coelho-Barros, J. Achcar, E. Martinez, N. Davarzani, H. Grabsch","doi":"10.15446/RCE.V42N2.76815","DOIUrl":"https://doi.org/10.15446/RCE.V42N2.76815","url":null,"abstract":"In this paper, we introduce a Bayesian approach for segmented Weibull distributions which could be a good alternative to analyze medical survival data in the presence of censored observations and covariates. With the obtained Bayesian estimated change-points we could get an excellent fit of the proposed model to any data sets. With the proposed methodology, it is also possible to identify survival times intervals where a covariate could have significantly different efects when compared to other lifetime intervals, an important point under a clinical view. The obtained Bayesian estimates are obtained using standard Markov Chain Monte Carlo methods. Some examples with real data sets illustrate the proposed methodology and its potential clinical value.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N2.76815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46917021","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}
Adolphus Wagala, G. González-Farías, Rogelio Ramos, Oscar Dalmau
{"title":"PLS Generalized Linear Regression and Kernel Multilogit Algorithm (KMA) for Microarray Data Classification Problem","authors":"Adolphus Wagala, G. González-Farías, Rogelio Ramos, Oscar Dalmau","doi":"10.15446/rce.v43n2.81811","DOIUrl":"https://doi.org/10.15446/rce.v43n2.81811","url":null,"abstract":"This study involves the implentation of the extensions of the partial least squares generalized linear regression (PLSGLR) by combining it with logistic regression and linear discriminant analysis, to get a partial least squares generalized linear regression-logistic regression model (PLSGLR-log), and a partial least squares generalized linear regression-linear discriminant analysis model (PLSGLRDA). A comparative study of the obtained classifiers with the classical methodologies like the k-nearest neighbours (KNN), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), ridge partial least squares (RPLS), and support vector machines(SVM) is then carried out. Furthermore, a new methodology known as kernel multilogit algorithm (KMA) is also implemented and its performance compared with those of the other classifiers. The KMA emerged as the best classifier based on the lowest classification error rates compared to the others when applied to the types of data are considered; the un- preprocessed and preprocessed.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050674","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}
R. D. Silva, Frank Gomes-Silva, Manoel Wallace A. Ramos, G. Cordeiro, P. Marinho, Thiago A. N. de Andrade
{"title":"The Exponentiated Kumaraswamy-G Class: General Properties and Application","authors":"R. D. Silva, Frank Gomes-Silva, Manoel Wallace A. Ramos, G. Cordeiro, P. Marinho, Thiago A. N. de Andrade","doi":"10.15446/RCE.V42N1.66205","DOIUrl":"https://doi.org/10.15446/RCE.V42N1.66205","url":null,"abstract":"We propose a new family of distributions called the exponentiated Kumaraswamy-G class with three extra positive parameters, which generalizes the Cordeiro and de Castro's family. Some special distributions in the new class are discussed. We derive some mathematical properties of the proposed class including explicit expressions for the quantile function, ordinary and incomplete moments, generating function, mean deviations, reliability, Rényi entropy and Shannon entropy. The method of maximum likelihood is used to fit the distributions in the proposed class. Simulations are performed in order to assess the asymptotic behavior of the maximum likelihood estimates. We illustrate its potentiality with applications to two real data sets which show that the extended Weibull model in the new class provides a better fit than other generalized Weibull distributions.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N1.66205","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44393012","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":"A Bayesian Approach to Mixed Gamma Regression Models","authors":"Marta Lucia Corrales, Edilberto Cepeda-Cuervo","doi":"10.15446/RCE.V42N1.69334","DOIUrl":"https://doi.org/10.15446/RCE.V42N1.69334","url":null,"abstract":"Gamma regression models are a suitable choice to model continuous variables that take positive real values. This paper presents a gamma regression model with mixed effects from a Bayesian approach. We use the parametrisation of the gamma distribution in terms of the mean and the shape parameter, both of which are modelled through regression structures that may involve fixed and random effects. A computational implementation via Gibbs sampling is provided and illustrative examples (simulated and real data) are presented.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N1.69334","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050546","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}
J. R. Tovar-Cuevas, Jennyfer Portilla-Yela, J. Achcar
{"title":"Method to Select Copula Functions","authors":"J. R. Tovar-Cuevas, Jennyfer Portilla-Yela, J. Achcar","doi":"10.15446/RCE.V42N1.71780","DOIUrl":"https://doi.org/10.15446/RCE.V42N1.71780","url":null,"abstract":"Copula functions have been extensively used in applied statistics, becoming a good alternative for modeling the dependence of multivariate data. Each copula function has a different dependence structure. An important issue in these applications is the choice of an appropriate copula function model for each one; thus common classical or Bayesian discrimination methods might not be appropriate for determining the best copula. Considering only the special case of bivariate data, we propose a procedure obtained from a recently introduced dependence measure for selecting an appropriate copula for the statistical data analyses.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N1.71780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46477367","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":"Some Recent Developments in Inference for Geostatistical Functional Data","authors":"P. Kokoszka, M. Reimherr","doi":"10.15446/RCE.V42N1.77058","DOIUrl":"https://doi.org/10.15446/RCE.V42N1.77058","url":null,"abstract":"We review recent developments related to inferencefor functions defined at spatial locations. We also considertime series of functions defined at irregularly distributedspatial points or on a grid. We focus on kriging, estimationof the functional mean and principal components, and significancetesting, giving special attention to testing spatio--temporalseparability in the context of functional data. We also highlightsome ideas related to extreme value theory for spatially indexed functionaltime series.","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15446/RCE.V42N1.77058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050600","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":"Modeling Data With Semicompeting Risks: An Application to Chronic Kidney Disease in Colombia","authors":"E. G. Patiño, G. Tunes, M. I. Múnera","doi":"10.15446/RCE.V42N1.68572","DOIUrl":"https://doi.org/10.15446/RCE.V42N1.68572","url":null,"abstract":"In this paper, the structure of semicompeting risks data, dened by Fine, Jiang & Chappell (2001), is studied. Two events are of interest: a nonterminal and a terminal event, the last one, can censor the non-terminal event, but not vice versa. Due to the possible dependence between the times until the occurrence of such events, two approaches are evaluated: modelling the bivariate survival function through Archimedean copulas and a shared frailty model. A simulation is conducted to examine its performance and both approaches are applied to a real data set of patients with chronic kidney disease (CKD).","PeriodicalId":54477,"journal":{"name":"Revista Colombiana De Estadistica","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67050969","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}