2 10 11 https://repository.horizon.ac.id/files/original/7e9097a2192dd6d1b18b1e84089e644e.pdf bbfbf87be288f8fa40ec1d02841a603d 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 109 Tahun 2024 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v109 Date A point or period of time associated with an event in the lifecycle of the resource 2024 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 English Type The nature or genre of the resource Text 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 bizicount: Bivariate Zero-Inflated Count Copula Regression Using R Subject The topic of the resource zero-inflated, bivariate, copula, Poisson, negative binomial, regression, R Description An account of the resource Two common issues arise in regression modelling of bivariate count data: (i) dependence across outcomes, and (ii) excess zero counts (i.e., zero inflation). However, there are currently few options to estimate bivariate zero-inflated count regression models in R. Therefore, we present an R package, bizicount, that enables researchers to easily estimate bivariate zero-inflated count copula regression models. By using copulas to model the dependence across outcomes, researchers do not have to make assumptions about the multivariate (and zero-inflated) structure relating their count variables to one another. Instead, they are only required to make familiar assumptions about the marginal distribution of each outcome variable, which should enable wider use of our approach. Below we present our proposed estimator, detail its advantages over existing alternatives, and demonstrate the use of the corresponding functions for bivariate modeling of terrorism data from Nigeria. Creator An entity primarily responsible for making the resource John M. Niehaus Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v109i01 Publisher An entity responsible for making the resource available Texas A&M University Date A point or period of time associated with an event in the lifecycle of the resource May 2024 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 English Type The nature or genre of the resource Text