1 10 15 https://repository.horizon.ac.id/files/original/5b1b0ad0b59671779265efd45f99c996.pdf 6b19410965dcddc7b83411cb400cac10 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 Most Likely Transformations: The mlt Package Subject The topic of the resource Transformation model, Transformation analysis Description An account of the resource The mlt package implements maximum likelihood estimation in the class of conditional transformation models. Based on a suitable explicit parameterization of the unconditional or conditional transformation function using infrastructure from package basefun, we show how one can define, estimate, and compare a cascade of increasingly complex transformation models in the maximum likelihood framework. Models for the unconditional or conditional distribution function of any univariate response variable are set-up and estimated in the same computational framework simply by choosing an appropriate transformation function and parameterization thereof. As it is computationally cheap to evaluate the distribution function, models can be estimated by maximization of the exact likelihood, especially in the presence of random censoring or truncation. The relatively dense high-level implementation in the R system for statistical computing allows generalization of many established implementations of linear transformation models, such as the Cox model or other parametric models for the analysis of survival or ordered categorical data, to the more complex situations illustrated in this paper Creator An entity primarily responsible for making the resource Torsten Hothorn Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i01 Publisher An entity responsible for making the resource available Universität Zürich 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/646c6864183470bbc0b52f24191f7b23.pdf a64cb781857506bdd8d00b5333b5fa32 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 Calculus of M-Estimation in R with geex Subject The topic of the resource empirical sandwich variance estimator, estimating equations, M-estimation, robust statistics, R Description An account of the resource M-estimation, or estimating equation, methods are widely applicable for point estimation and asymptotic inference. In this paper, we present an R package that can find roots and compute the empirical sandwich variance estimator for any set of user-specified, unbiased estimating equations. Examples from the M-estimation primer by Stefanski and Boos (2002) demonstrate use of the software. The package also includes a framework for finite sample, heteroscedastic, and autocorrelation variance corrections, and a website with an extensive collection of tutorials. Creator An entity primarily responsible for making the resource Bradley C. Saul Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i02 Publisher An entity responsible for making the resource available NoviSci 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/da63c8ca8656c2705cc75c05c97391d8.pdf 01284f6530fa2c34349069c21303c4d0 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 PAFit: An R Package for the Non-Parametric Estimation of Preferential Attachment and Node Fitness in Temporal Complex Networks Subject The topic of the resource temporal networks, dynamic networks, preferential attachment, fitness, rich-getricher, fit-get-richer, R, C++ Description An account of the resource Many real-world systems are profitably described as complex networks that grow over time. Preferential attachment and node fitness are two simple growth mechanisms that not only explain certain structural properties commonly observed in real-world systems, but are also tied to a number of applications in modeling and inference. While there are statistical packages for estimating various parametric forms of the preferential attachment function, there is no such package implementing non-parametric estimation procedures. The non-parametric approach to the estimation of the preferential attachment function allows for comparatively finer-grained investigations of the “rich-get-richer” phenomenon that could lead to novel insights in the search to explain certain nonstandard structural properties observed in real-world networks. This paper introduces the R package PAFit, which implements non-parametric procedures for estimating the preferential attachment function and node fitnesses in a growing network, as well as a number of functions for generating complex networks from these two mechanisms. The main computational part of the package is implemented in C++ with OpenMP to ensure scalability to large-scale networks. In this paper, we first introduce the main functionalities of PAFit through simulated examples, and then use the package to analyze a collaboration network between scientists in the field of complex networks. The results indicate the joint presence of “richget-richer” and “fit-get-richer” phenomena in the collaboration network. The estimated attachment function is observed to be near-linear, which we interpret as meaning that the chance an author gets a new collaborator is proportional to their current number of collaborators. Furthermore, the estimated author fitnesses reveal a host of familiar faces from the complex networks community among the field’s topmost fittest network scientist Creator An entity primarily responsible for making the resource Thong Pham Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i03 Publisher An entity responsible for making the resource available RIKEN Center for AIP 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 https://repository.horizon.ac.id/files/original/56d1cbd2564295b0db3f38a9a7dbeab4.pdf 93a1a565f8fe5b3ed94841dd998f5e32 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 Integration of R and Scala Using rscala Subject The topic of the resource Java virtual machine (JVM), language bridges, R, Scala Description An account of the resource The rscala software is a simple, two-way bridge between R and Scala that allows users to leverage the unique strengths of both languages in a single project. Scala classes can be instantiated from R and Scala methods can be called. Arbitrary Scala code can be executed on-the-fly from within R and callbacks to R are supported. R packages can be developed based on Scala. Conversely, rscala also enables R code to be embedded within a Scala application. The rscala package is available from the Comprehensive R Archive Network (CRAN) and has no dependencies beyond base R and the Scala standard library. Creator An entity primarily responsible for making the resource David B. Dahl Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i04 Publisher An entity responsible for making the resource available Brigham Young 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 https://repository.horizon.ac.id/files/original/4a459c7d1440e10eb98ea6d2cfc92cae.pdf 146da754b39cd56874b8c3d94bdd5b73 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 BPEC: An R Package for Bayesian Phylogeographic and Ecological Clustering Subject The topic of the resource statistical phylogeography, biogeography, population genetics, Bayesian computation, R. Description An account of the resource BPEC is an R package for Bayesian phylogeographic and ecological clustering which allows geographical, environmental and phenotypic measurements to be combined with deoxyribonucleic acid (DNA) sequences in order to reveal geographic structuring of DNA sequence clusters consistent with migration events. DNA sequences are modelled using a collapsed version of a simplified coalescent model projected onto haplotype trees, which subsequently give rise to constrained clusterings as migrations occur. Within each cluster, a multivariate Gaussian distribution of the covariates (geographical, environmental, phenotypic) is used. Inference follows tailored reversible jump Markov chain Monte Carlo sampling so that the number of clusters (i.e., migrations) does not need to be pre-specified. A number of output plots and visualizations are provided which reflect the posterior distribution of the parameters of interest. BPEC also includes functions that create output files which can be loaded into Google Earth. The package commands are illustrated through an example dataset of the polytypic Near Eastern brown frog Rana macrocnemis analyzed using BPEC Creator An entity primarily responsible for making the resource Ioanna Manolopoulou Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v092i05 Publisher An entity responsible for making the resource available University College London 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 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/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/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/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