2 10 14 https://repository.horizon.ac.id/files/original/b28c82eff65045599841453b596530d7.pdf b4a269799a4a4ea014c36c04984416ee Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 93 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v093 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource mvord: An R Package for Fitting Multivariate Ordinal Regression Models Subject The topic of the resource composite likelihood estimation, correlated ordinal data, multivariate ordinal logit regression model, multivariate ordinal probit regression model, R. Description An account of the resource The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link. A flexible modeling framework for multiple ordinal measurements on the same subject is set up, which takes into consideration the dependence among the multiple observations by employing different error structures. Heterogeneity in the error structure across the subjects can be accounted for by the package, which allows for covariate dependent error structures. In addition, different regression coefficients and threshold parameters for each response are supported. If a reduction of the parameter space is desired, constraints on the threshold as well as on the regression coefficients can be specified by the user. The proposed multivariate framework is illustrated by means of a credit risk application. Creator An entity primarily responsible for making the resource Rainer Hirk Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v093i04 Publisher An entity responsible for making the resource available WU Wirtschaftsuniversität Wien Date A point or period of time associated with an event in the lifecycle of the resource April 2020 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Inggris Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/8c37bc3f242971de80950a5e08175190.pdf 3eb49e0a5dfda92baa1522e3b767af24 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 93 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v093 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource lmSubsets: Exact Variable-Subset Selection in Linear Regression for R Subject The topic of the resource linear regression, model selection, variable selection, best-subset regression, R Description An account of the resource An R package for computing the all-subsets regression problem is presented. The proposed algorithms are based on computational strategies recently developed. A novel algorithm for the best-subset regression problem selects subset models based on a predetermined criterion. The package user can choose from exact and from approximation algorithms. The core of the package is written in C++ and provides an efficient implementation of all the underlying numerical computations. A case study and benchmark results illustrate the usage and the computational efficiency of the package. Creator An entity primarily responsible for making the resource Marc Hofmann Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v093i03 Publisher An entity responsible for making the resource available University of Oviedo Cyprus University of Technology Date A point or period of time associated with an event in the lifecycle of the resource April 2020 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Inggris Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/07bb96c3a76a762a9e5c1d724b0547f4.pdf 60ff30b7988595fa9d8e0aef04e2c3a7 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 93 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v093 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Semi-Parametric Joint Modeling of Survival and Longitudinal Data: The R Package JSM Subject The topic of the resource B-splines, EM algorithm, multiplicative random effects, semi-parametric models, transformation model. Description An account of the resource This paper is devoted to the R package JSM which performs joint statistical modeling of survival and longitudinal data. In biomedical studies it has been increasingly common to collect both baseline and longitudinal covariates along with a possibly censored survival time. Instead of analyzing the survival and longitudinal outcomes separately, joint modeling approaches have attracted substantive attention in the recent literature and have been shown to correct biases from separate modeling approaches and enhance information. Most existing approaches adopt a linear mixed effects model for the longitudinal component and the Cox proportional hazards model for the survival component. We extend the Cox model to a more general class of transformation models for the survival process, where the baseline hazard function is completely unspecified leading to semiparametric survival models. We also offer a non-parametric multiplicative random effects model for the longitudinal process in JSM in addition to the linear mixed effects model. In this paper, we present the joint modeling framework that is implemented in JSM, as well as the standard error estimation methods, and illustrate the package with two real data examples: a liver cirrhosis data and a Mayo Clinic primary biliary cirrhosis data Creator An entity primarily responsible for making the resource Cong Xu Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v093i02 Publisher An entity responsible for making the resource available Southern University of Science and Technology Date A point or period of time associated with an event in the lifecycle of the resource April 2020 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Inggris Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/39f684ce4528bf3969e4f8db5fe70d5f.pdf 1d55326d5eb8d2681992dcff978aae61 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 93 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v093 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ManifoldOptim: An R Interface to the ROPTLIB Library for Riemannian Manifold Optimization Subject The topic of the resource manifold, Riemannian, Grassmann, Stiefel, Euclidean, optimization. Description An account of the resource Manifold optimization appears in a wide variety of computational problems in the applied sciences. In recent statistical methodologies such as sufficient dimension reduction and regression envelopes, estimation relies on the optimization of likelihood functions over spaces of matrices such as the Stiefel or Grassmann manifolds. Recently, Huang, Absil, Gallivan, and Hand (2016) have introduced the library ROPTLIB, which provides a framework and state of the art algorithms to optimize real-valued objective functions over commonly used matrix-valued Riemannian manifolds. This article presents ManifoldOptim, an R package that wraps the C++ library ROPTLIB. ManifoldOptim enables users to access functionality in ROPTLIB through R so that optimization problems can easily be constructed, solved, and integrated into larger R codes. Computationally intensive problems can be programmed with Rcpp and RcppArmadillo, and otherwise accessed through R. We illustrate the practical use of ManifoldOptim through several motivating examples involving dimension reduction and envelope methods in regression. Creator An entity primarily responsible for making the resource Sean R. Martin Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v093i01 Publisher An entity responsible for making the resource available University of Maryland, Baltimore County Date A point or period of time associated with an event in the lifecycle of the resource February 2020 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Inggris Type The nature or genre of the resource Text