1 10 15 https://repository.horizon.ac.id/files/original/ae00fae8891d1b4c21822c6db52c4438.pdf 71a135b2ee180d6c4543a58347aedb5c 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 R Graphics (3rd Edition) Subject The topic of the resource Graphic Description An account of the resource It has been fourteen years since the first edition of R Graphics was published (Murrell 2006) and eight since the second one was released (Murrell 2012). For readers, like me, who read the first edition of R Graphics but skipped the second one, this third edition of R Graphics represents a new, fresh updated version of the book. In transit from the first to the third edition, in addition to including new material, Dr. Murrell has introduced key changes and some rearrangements that have made the whole book more understandable, especially the concepts related to viewports and coordinate systems. Creator An entity primarily responsible for making the resource Jose M. Pavía Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092b01 Publisher An entity responsible for making the resource available Universitat de València 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 https://repository.horizon.ac.id/files/original/e3638d35176cac9880763d96fe3ce1a8.pdf a93f84951565e6aa02a787635c6ec2a5 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 gdpc: An R Package for Generalized Dynamic Principal Components Subject The topic of the resource dimensionality reduction, high-dimensional time series, R. Description An account of the resource gdpc is an R package for the computation of the generalized dynamic principal components proposed in Peña and Yohai (2016). In this paper, we briefly introduce the problem of dynamical principal components, propose a solution based on a reconstruction criteria and present an automatic procedure to compute the optimal reconstruction. This solution can be applied to the non-stationary case, where the components need not be a linear combination of the observations, as is the case in the proposal of Brillinger (1981). This article discusses some new features that are included in the package and that were not considered in Peña and Yohai (2016). The most important one is an automatic procedure for the identification of both the number of lags to be used in the generalized dynamic principal components as well as the number of components required for a given reconstruction accuracy. These tools make it easy to use the proposed procedure in large data sets. The procedure can also be used when the number of series is larger than the number of observations. We describe an iterative algorithm and present an example of the use of the package with real data Creator An entity primarily responsible for making the resource Daniel Peña Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092c02 Publisher An entity responsible for making the resource available Universidad Carlos III de Madrid 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 https://repository.horizon.ac.id/files/original/2fe14d23fc0c10e204399dcca468b366.pdf 1bf52bedb99059c68d487e8d97ee9979 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 Working with User Agent Strings in Stata: The parseuas Command Subject The topic of the resource user agent string, web surveys, device detection, browser, paradata, Stata. Description An account of the resource With the rising popularity of web surveys and the increasing use of paradata by survey methodologists, assessing information stored in user agent strings becomes inevitable. These data contain meaningful information about the browser, operating system, and device that a survey respondent uses. This article provides an overview of user agent strings, their specific structure and history, how they can be obtained when conducting a web survey, as well as what kind of information can be extracted from the strings. Further, the user written command parseuas is introduced as an efficient means to gather detailed information from user agent strings. The application of parseuas is illustrated by an example that draws on a pooled data set consisting of 29 web surveys. Creator An entity primarily responsible for making the resource Joss Roßmann Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092c01 Publisher An entity responsible for making the resource available GESIS – Leibniz Institute for the Social Sciences 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 https://repository.horizon.ac.id/files/original/1ebb480487c044b9910c8ae1428a64dd.pdf 10a59c1be535ac6170e92183840f55ed 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 Fitting Prediction Rule Ensembles with R Package pre Subject The topic of the resource prediction rules, ensemble learning, decision trees, lasso penalty, R Description An account of the resource Prediction rule ensembles (PREs) are sparse collections of rules, offering highly interpretable regression and classification models. This paper shows how they can be fitted using function pre from R package pre, which derives PREs largely through the methodology of Friedman and Popescu (2008). The implementation and functionality of pre is described and illustrated through application on a dataset on the prediction of depression. Furthermore, accuracy and sparsity of pre is compared with that of single trees, random forests, lasso regression and the original RuleFit implementation of Friedman and Popescu (2008) in four benchmark datasets. Results indicate that pre derives ensembles with predictive accuracy similar to that of random forests, while using a smaller number of variables for prediction. Furthermore, pre provided better accuracy and sparsity than the original RuleFit implementation Creator An entity primarily responsible for making the resource Marjolein Fokkema Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i12 Publisher An entity responsible for making the resource available Universiteit Leiden 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 https://repository.horizon.ac.id/files/original/d5533428cdb2296adebbb09fc3bbd436.pdf 663531e073a0f71ffa0542d9796d41a9 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 Algebraic Analysis of Multiple Social Networks with multiplex Subject The topic of the resource social network analysis, relational algebra, graph visualization, R Description An account of the resource multiplex is a computer program that provides algebraic tools for the analysis of multiple network structures within the R environment. Apart from the possibility to create and manipulate multivariate data representing multiplex, signed, and two-mode networks, this package offers a collection of functions that deal with algebraic systems – such as the partially ordered semigroup, and balance or cluster semirings – their decomposition, and the enumeration of bundle patterns occurring at different levels of the network. Moreover, through Galois derivations between families of the pairs of subsets in different domains it is possible to analyze affiliation networks with an algebraic approach. Visualization of multigraphs, different forms of bipartite graphs, inclusion lattices, Cayley graphs is supported as well with related packages Creator An entity primarily responsible for making the resource J. Antonio Rivero Ostoic Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i11 Publisher An entity responsible for making the resource available Antonio Rivero Ostoic Aarhus University 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 https://repository.horizon.ac.id/files/original/e43c4e1f2ccec8f77c97bbebe2121ef6.pdf 2f1acd8644dd030dda60d7a1243c3e8b 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 bridgesampling: An R Package for Estimating Normalizing Constants Subject The topic of the resource bridge sampling, marginal likelihood, model selection, Bayes factor, Warp-III Description An account of the resource Statistical procedures such as Bayes factor model selection and Bayesian model averaging require the computation of normalizing constants (e.g., marginal likelihoods). These normalizing constants are notoriously difficult to obtain, as they usually involve highdimensional integrals that cannot be solved analytically. Here we introduce an R package that uses bridge sampling (Meng and Wong 1996; Meng and Schilling 2002) to estimate normalizing constants in a generic and easy-to-use fashion. For models implemented in Stan, the estimation procedure is automatic. We illustrate the functionality of the package with three examples. Creator An entity primarily responsible for making the resource Quentin F. Gronau Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i10 Publisher An entity responsible for making the resource available University of Amsterdam 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 https://repository.horizon.ac.id/files/original/1befd5ccc02716b3cdd1889072ed1a5a.pdf 351f9e87f8dd48dae01df3618d8ecfb2 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 spBayesSurv: Fitting Bayesian Spatial Survival Models Using R Subject The topic of the resource Bayesian nonparametric, survival analysis, spatial dependence, semiparametric models, parametric models Description An account of the resource Spatial survival analysis has received a great deal of attention over the last 20 years due to the important role that geographical information can play in predicting survival. This paper provides an introduction to a set of programs for implementing some Bayesian spatial survival models in R using the package spBayesSurv. The function survregbayes includes the three most commonly-used semiparametric models: proportional hazards, proportional odds, and accelerated failure time. All manner of censored survival times are simultaneously accommodated including uncensored, interval censored, current-status, left and right censored, and mixtures of these. Left-truncated data are also accommodated. Time-dependent covariates are allowed under the piecewise constant assumption. Both georeferenced and areally observed spatial locations are handled via frailties. Model fit is assessed with conditional Cox-Snell residual plots, and model choice is carried out via the log pseudo marginal likelihood, the deviance information criterion and the WatanabeAkaike information criterion. The accelerated failure time frailty model with a covariatedependent baseline is included in the function frailtyGAFT. In addition, the package also provides two marginal survival models: proportional hazards and linear dependent Dirichlet process mixtures, where the spatial dependence is modeled via spatial copulas. Note that the package can also handle non-spatial data using non-spatial versions of the aforementioned models. Creator An entity primarily responsible for making the resource Haiming Zhou Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i09 Publisher An entity responsible for making the resource available Northern Illinois University 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 https://repository.horizon.ac.id/files/original/403b03f77a8a4a710dce7faebab73a17.pdf 72643fd8372d7cc53364155fd7159c89 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 Computing the Oja Median in R: The Package OjaNP Subject The topic of the resource Oja median, Oja signs, Oja signed ranks, Oja ranks, R, C++. Description An account of the resource The Oja median is one of several extensions of the univariate median to the multivariate case. It has many desirable properties, but is computationally demanding. In this paper, we first review the properties of the Oja median and compare it to other multivariate medians. Then, we discuss four algorithms to compute the Oja median, which are implemented in our R package OjaNP. Besides these algorithms, the package contains also functions to compute Oja signs, Oja signed ranks, Oja ranks, and the related scatter concepts. To illustrate their use, the corresponding multivariate one- and C-sample location tests are implemented. Creator An entity primarily responsible for making the resource Klaus Nordhausen Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i08 Publisher An entity responsible for making the resource available Vienna University of Technology 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 https://repository.horizon.ac.id/files/original/798011aa630dfcba5784e641cb133cc9.pdf 0c2ce15a1548a48d8e97cb1797e820af 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 SQUAREM: An R Package for Off-the-Shelf Acceleration of EM, MM and Other EM-Like Monotone Algorithms Subject The topic of the resource EM algorithm, fixed-point iteration, monotone convergence, convergence acceleration, optimization, high dimensional models, extrapolation methods Description An account of the resource We discuss the R package SQUAREM for accelerating iterative algorithms which exhibit slow, monotone convergence. These include the well-known expectation-maximization algorithm, majorize-minimize (MM), and other EM-like algorithms such as expectation conditional maximization, and generalized EM algorithms. We demonstrate the simplicity, generality, and power of SQUAREM through a wide array of applications of EM/MM problems, including binary Poisson mixture, factor analysis, interval censoring, genetics admixture, and logistic regression maximum likelihood estimation (an MM problem). We show that SQUAREM is easy to apply, and can accelerate any fixed-point, smooth, contraction mapping with linear convergence rate. The squared iterative scheme (SQUAREM) algorithm provides significant speed-up of EM-like algorithms. The margin of the advantage for SQUAREM is especially huge for high-dimensional problems or when the EM step is relatively time-consuming to evaluate. SQUAREM can be used off-the-shelf since there is no need for the user to tweak any control parameters to optimize performance. Given its remarkable ease of use, SQUAREM may be considered as a default accelerator for slowly converging EM-like algorithms. All the comparisons of CPU computing time in the paper are made on a quad-core 2.3 GHz Intel Core i7 Mac computer. R package SQUAREM is available from the Comprehensive R Archive Network (CRAN) at https://CRAN.R-project.org/package=SQUAREM/. Creator An entity primarily responsible for making the resource Yu Du Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i07 Publisher An entity responsible for making the resource available Johns Hopkins University 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 https://repository.horizon.ac.id/files/original/df55cce1c352e91822908c089a77b225.pdf b08d4aea0d8e4c233447546e4987e198 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 92 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v092 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 The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition Subject The topic of the resource MOEA/D, multiobjective evolutionary algorithms, R, component-oriented design Description An account of the resource Multiobjective evolutionary algorithms based on decomposition (MOEA/D) represent a widely used class of population-based metaheuristics for the solution of multicriteria optimization problems. We introduce the MOEADr package, which offers many of these variants as instantiations of a component-oriented framework. This approach contributes for easier reproducibility of existing MOEA/D variants from the literature, as well as for faster development and testing of new composite algorithms. The package offers an standardized, modular implementation of MOEA/D based on this framework, which was designed aiming at providing researchers and practitioners with a standard way to discuss and express MOEA/D variants. In this paper we introduce the design principles behind the MOEADr package, as well as its current components. Three case studies are provided to illustrate the main aspects of the package Creator An entity primarily responsible for making the resource Felipe Campelo Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i06 Publisher An entity responsible for making the resource available Aston University 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 Indonesia Type The nature or genre of the resource Text