1 10 12 https://repository.horizon.ac.id/files/original/ef07f083f32c52a04cbf4747fc6a29a7.pdf d842044daf63af87a80bc0bd9ee69bf1 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 BAMBI: An R Package for Fitting Bivariate Angular Mixture Models Subject The topic of the resource angular data, mixture models, bivariate data, von Mises distribution, wrapped normal distribution, R, Hamiltonian Monte Carlo, MCMC, Gibbs sampler Description An account of the resource Statistical analyses of directional or angular data have applications in a variety of fields, such as geology, meteorology and bioinformatics. There is substantial literature on descriptive and inferential techniques for univariate angular data, with the bivariate (or more generally, multivariate) cases receiving more attention in recent years. More specifically, the bivariate wrapped normal, von Mises sine and von Mises cosine distributions, and mixtures thereof, have been proposed for practical use. However, there is a lack of software implementing these distributions and the associated inferential techniques. In this article, we introduce BAMBI, an R package for analyzing bivariate (and univariate) angular data. We implement random data generation, density evaluation, and computation of theoretical summary measures (variances and correlation coefficients) for the three aforementioned bivariate angular distributions, as well as two univariate angular distributions: the univariate wrapped normal and the univariate von Mises distribution. The major contribution of BAMBI to statistical computing is in providing Bayesian methods for modeling angular data using finite mixtures of these distributions. We also provide functions for visual and numerical diagnostics and Bayesian inference for the fitted models. In this article, we first provide a brief review of the distributions and techniques used in BAMBI, then describe the capabilities of the package, and finally conclude with demonstrations of mixture model fitting using BAMBI on the two real data sets included in the package, one univariate and one bivariate Creator An entity primarily responsible for making the resource Saptarshi Chakraborty Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i11 Publisher An entity responsible for making the resource available State University of New York at Buffalo Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/a12337d87ecb6e2ff65bf5d888eefa65.pdf 26f85393fc3bdfcd6d7d9d7ffcc8f445 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-Based Approach Subject The topic of the resource causality, do-calculus, selection bias, transportability, missing data, case-control design, meta-analysis Description An account of the resource Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but important extensions that have not been considered in the literature such as combined transportability and selection bias, or multiple sources of selection bias. To tackle these new settings, we present a search algorithm directly over the rules of do-calculus. Due to the generality of do-calculus, the search is capable of taking more advanced datagenerating mechanisms into account along with an arbitrary type of both observational and experimental source distributions. The search is enhanced via a heuristic and search space reduction techniques. The approach, called do-search, is provably sound, and it is complete with respect to identifiability problems that have been shown to be completely characterized by do-calculus. When extended with additional rules, the search is capable of handling missing data problems as well. With the versatile search, we are able to approach new problems for which no other algorithmic solutions exist. We perform a systematic analysis of bivariate missing data problems and study causal inference under case-control design. We also present the R package dosearch that provides an interface for a C++ implementation of the search. Creator An entity primarily responsible for making the resource Santtu Tikka Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i05 Publisher An entity responsible for making the resource available University of Jyvaskyla Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/d50ec621f2caf407d79593df7619f388.pdf c6bf6a1064dca42ffafa0eba304f1987 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 cold: An R Package for the Analysis of Count Longitudinal Data Subject The topic of the resource count longitudinal data, exact likelihood, Markov chain, marginal models, random effects models Description An account of the resource This paper describes the R package cold for the analysis of count longitudinal data. In this package marginal and random effects models are considered. In both cases estimation is via maximization of the exact likelihood and serial dependence among observations is assumed to be of Markovian type and referred as the integer-valued autoregressive of order one process. For random effects models adaptive Gaussian quadrature and Monte Carlo methods are used to compute integrals whose dimension depends on the structure of random effects. cold is written partly in R language, partly in Fortran 77, interfaced through R and is built following the S4 formulation of R methods Creator An entity primarily responsible for making the resource M. Helena Gonçalves Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i03 Publisher An entity responsible for making the resource available Universidade do Algarve Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/193c6ba39c476e2cf4eca701a23685f7.pdf da5715e310e8255bf2324ca759e2dcaa 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 Conditional Model Selection in Mixed-Effects Models with cAIC4 Subject The topic of the resource conditional AIC, lme4, mixed-effects models, penalized splines. Description An account of the resource Model selection in mixed models based on the conditional distribution is appropriate for many practical applications and has been a focus of recent statistical research. In this paper we introduce the R package cAIC4 that allows for the computation of the conditional Akaike information criterion (cAIC). Computation of the conditional AIC needs to take into account the uncertainty of the random effects variance and is therefore not straightforward. We introduce a fast and stable implementation for the calculation of the cAIC for (generalized) linear mixed models estimated with lme4 and (generalized) additive mixed models estimated with gamm4. Furthermore, cAIC4 offers a stepwise function that allows for an automated stepwise selection scheme for mixed models based on the cAIC. Examples of many possible applications are presented to illustrate the practical impact and easy handling of the package. Creator An entity primarily responsible for making the resource Benjamin Säfken Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i08 Publisher An entity responsible for making the resource available Georg-August Universität Göttingen Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/8bbc253ae88f5d9075c4f59fafc16afe.pdf f9367871d831edfe980e3d880a89369d 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data Subject The topic of the resource : functional data analysis, 4D data, climate data, environmetrics, EM algorithm Description An account of the resource Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time. The MATLAB D-STEM v1 software package was first introduced for modeling multivariate space-time data and has been recently extended to D-STEM v2 to handle functional data indexed across space and over time. This paper introduces the new modeling capabilities of DSTEM v2 as well as the complexity reduction techniques required when dealing with large data sets. Model estimation, validation and dynamic kriging are demonstrated in two case studies, one related to ground-level air quality data in Beijing, China, and the other one related to atmospheric profile data collected globally through radio sounding Creator An entity primarily responsible for making the resource Yaqiong Wang Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i10 Publisher An entity responsible for making the resource available Peking University Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/002e9f8109cfb95346b4ea4385687f8e.pdf 3cc1e37e02db3da2850a555419046803 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Still Image A static visual representation. Examples include paintings, drawings, graphic designs, plans and maps. Recommended best practice is to assign the type Text to images of textual materials. 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 dynamichazard: Dynamic Hazard Models Using State Space Models Subject The topic of the resource survival analysis, time-varying parameters, extended Kalman filter, EM algorithm, unscented Kalman filter, parallel computing, R, Rcpp, RcppArmadillo. Description An account of the resource The dynamichazard package implements state space models that can provide a computationally efficient way to model time-varying parameters in survival analysis. I cover the models and some of the estimation methods implemented in dynamichazard, apply them to a large data set, and perform a simulation study to illustrate the methods’ computation time and performance. One of the methods is compared with other models implemented in R which allow for left-truncation, right-censoring, time-varying covariates, and timevarying parameters. Creator An entity primarily responsible for making the resource Benjamin Christoffersen Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i07 Publisher An entity responsible for making the resource available Copenhagen Business School Date A point or period of time associated with an event in the lifecycle of the resource august 2021 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/ce929cade83efc5c3319eaacb734e6f7.pdf c0c15e9cfb436a82269fc0f7c920732f 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 IncDTW: An R Package for Incremental Calculation of Dynamic Time Warping Subject The topic of the resource : dynamic time warping, time series, k-NN, subsequence matching, distance measure, clustering, classification Description An account of the resource Dynamic time warping (DTW) is a popular distance measure for time series analysis and has been applied in many research domains. This paper proposes the R package IncDTW for the incremental calculation of DTW, and based on this principle IncDTW also helps to classify or cluster time series, or perform subsequence matching and k-nearest neighbor search. DTW can measure dissimilarity between two temporal sequences which may vary in speed, with a major downside of high computational costs. Especially for analyzing live data streams, subsequence matching or calculating pairwise distance matrices, runtime intensive computations are unfavorable or can even make the analysis intractable. IncDTW tackles this problem by a vector-based implementation of the DTW algorithm to reduce the space complexity from a quadratic to a linear level in number of observations, and an incremental calculation of DTW for updating interim results to reduce the runtime complexity for online applications. We discuss the fundamental functionalities of IncDTW and apply the package to classify multivariate live stream accelerometer time series for activity recognition. Finally, comparative runtime experiments with various R and Python packages for various data analysis tasks emphasize the broad applicability of IncDTW. Creator An entity primarily responsible for making the resource Maximilian Leodolter Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i09 Publisher An entity responsible for making the resource available Austrian Institute of Technology Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/91d790e12484be2204b647778c435eaf.pdf 17ed86ca2d023c50713828a61b4559a3 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 Optimal Design Generation and Power Evaluation in R: The skpr Package Subject The topic of the resource design of experiments, optimal design, power, R. Description An account of the resource The R package skpr provides a suite of functions to generate and evaluate experimental designs. Package skpr generates D, I, Alias, A, E, T, and G-optimal designs, and supports custom user-defined optimality criteria, N-level split-plot designs, mixture designs, and design augmentation. Also included are a collection of analytic and Monte Carlo power evaluation functions for normal, non-normal, random effects, and survival models, as well as tools to plot fraction of design space plots and correlation maps. Additionally, skpr includes a flexible framework for the user to perform custom power analyses with external libraries and user-defined functions, as well as a graphical user interface that wraps most of the functionality of the package in a point-and-click web application. Creator An entity primarily responsible for making the resource Tyler Morgan-Wall Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i01 Publisher An entity responsible for making the resource available Institute for Defense Analyses Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/90d1c55f7c7c538d00a83f7d569c22fb.pdf fd71cf556ad798a80ffa1e3c3a7ac3ef 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 Regularized Ordinal Regression and the ordinalNet R Package Subject The topic of the resource ordinal regression, multinomial regression, variable selection, lasso, elastic net Description An account of the resource Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression models are widely used in applications where the use of regularization could be beneficial; however, these models are not included in many popular software packages for regularized regression. We propose a coordinate descent algorithm to fit a broad class of ordinal regression models with an elastic net penalty. Furthermore, we demonstrate that each model in this class generalizes to a more flexible form, that can be used to model either ordered or unordered categorical response data. We call this the elementwise link multinomial-ordinal class, and it includes widely used models such as multinomial logistic regression (which also has an ordinal form) and ordinal logistic regression (which also has an unordered multinomial form). We introduce an elastic net penalty class that applies to either model form, and additionally, this penalty can be used to shrink a non-ordinal model toward its ordinal counterpart. Finally, we introduce the R package ordinalNet, which implements the algorithm for this model class. Creator An entity primarily responsible for making the resource Michael J. Wurm Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i06 Publisher An entity responsible for making the resource available University of Wisconsin–Madison Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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/e6448acf6e0dc971e887334911f21c74.pdf 76a32e4b7f3eef9ac9e8c272ebfbcedb 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 99 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v099 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 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 Robust Analysis of Sample Selection Models through the R Package ssmrob Subject The topic of the resource endogenous treatment model, R, robust estimation, robust inference, sample selection models, two-step estimator Description An account of the resource The aim of this paper is to describe the implementation and to provide a tutorial for the R package ssmrob, which is developed for robust estimation and inference in sample selection and endogenous treatment models. The sample selectivity issue occurs in practice in various fields, when a non-random sample of a population is observed, i.e., when observations are present according to some selection rule. It is well known that the classical estimators introduced by Heckman (1979) are very sensitive to small deviations from the distributional assumptions (typically the normality assumption on the error terms). Zhelonkin, Genton, and Ronchetti (2016) investigated the robustness properties of these estimators and proposed robust alternatives to the estimator and the corresponding test. We briefly discuss the robust approach and demonstrate its performance in practice by providing several empirical examples. The package can be used both to produce a complete robust statistical analysis of these models which complements the classical one and as a set of useful tools for exploratory data analysis. Specifically, robust estimators and standard errors of the coefficients of both the selection and the regression equations are provided together with a robust test of selectivity. The package therefore provides additional useful information to practitioners in different fields of applications by enhancing their statistical analysis of these models. Creator An entity primarily responsible for making the resource Mikhail Zhelonkin Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v099i04 Publisher An entity responsible for making the resource available Erasmus University Rotterdam Date A point or period of time associated with an event in the lifecycle of the resource August 2021 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