1 10 16 https://repository.horizon.ac.id/files/original/8aaaeea0927221c764cebad968170ef3.pdf 4136dd22a88ffae51afc4e52ad5a6bce 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R Subject The topic of the resource : clustered data, covariance matrix estimator, object orientation, simulation, R. Description An account of the resource Clustered covariances or clustered standard errors are very widely used to account for correlated or clustered data, especially in economics, political sciences, and other social sciences. They are employed to adjust the inference following estimation of a standard least-squares regression or generalized linear model estimated by maximum likelihood. Although many publications just refer to “the” clustered standard errors, there is a surprisingly wide variety of clustered covariances, particularly due to different flavors of bias corrections. Furthermore, while the linear regression model is certainly the most important application case, the same strategies can be employed in more general models (e.g., for zero-inflated, censored, or limited responses). In R, functions for covariances in clustered or panel models have been somewhat scattered or available only for certain modeling functions, notably the (generalized) linear regression model. In contrast, an object-oriented approach to “robust” covariance matrix estimation – applicable beyond lm() and glm() – is available in the sandwich package but has been limited to the case of cross-section or time series data. Starting with sandwich 2.4.0, this shortcoming has been corrected: Based on methods for two generic functions (estfun() and bread()), clustered and panel covariances are provided in vcovCL(), vcovPL(), and vcovPC(). Moreover, clustered bootstrap covariances are provided in vcovBS(), using model update() on bootstrap samples. These are directly applicable to models from packages including MASS, pscl, countreg, and betareg, among many others. Some empirical illustrations are provided as well as an assessment of the methods’ performance in a simulation study Creator An entity primarily responsible for making the resource Achim Zeileis Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i01 Publisher An entity responsible for making the resource available Universität Innsbruck Date A point or period of time associated with an event in the lifecycle of the resource October 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/c33ea0ae38d2e3dd2db8653b01c76788.pdf a6286675b6924e71e466d7901a055cec 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Estimating Animal Abundance with N-Mixture Models Using the R-INLA Package for R Subject The topic of the resource : abundance, detection, JAGS, N-mixture model, R, R-INLA, unmarked, wildlife Description An account of the resource Successful management of wildlife populations requires accurate estimates of abundance. Abundance estimates can be confounded by imperfect detection during wildlife surveys. N-mixture models enable quantification of detection probability and, under appropriate conditions, produce abundance estimates that are less biased. Here, we demonstrate how to use the R-INLA package for R to analyze N-mixture models, and compare performance of R-INLA to two other common approaches: JAGS (via the runjags package for R), which uses Markov chain Monte Carlo and allows Bayesian inference, and the unmarked package for R, which uses maximum likelihood and allows frequentist inference. We show that R-INLA is an attractive option for analyzing N-mixture models when (i) fast computing times are necessary (R-INLA is 10 times faster than unmarked and 500 times faster than JAGS), (ii) familiar model syntax and data format (relative to other R packages) is desired, (iii) survey-level covariates of detection are not essential, and (iv) Bayesian inference is preferred Creator An entity primarily responsible for making the resource Timothy D. Meehan Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i02 Publisher An entity responsible for making the resource available National Audubon Society Date A point or period of time associated with an event in the lifecycle of the resource October 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/4d49f3d3e4fd55679527d54d2d4eb686.pdf 1febdfc95df22b51bd2227d93a070fb7 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 A Data Envelopment Analysis Toolbox for MATLAB Subject The topic of the resource data envelopment analysis, distance functions, technical efficiency, MATLAB Description An account of the resource The Data Envelopment Analysis Toolbox is a new package for MATLAB that includes functions to calculate the main data envelopment analysis models. The package includes code for the standard radial input, output and additive measures, allowing for constant and variable returns to scale, as well as recent developments related to the directional distance function, and including both desirable and undesirable outputs when measuring efficiency and productivity; i.e., Malmquist and Malmquist-Luenberger indices. Bootstrapping to perform statistical analysis is also included. This paper describes the methodology and implementation of the functions, and reports numerical results using a reliable productivity database on US agriculture to illustrate their use Creator An entity primarily responsible for making the resource José L. Zofío Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i03 Publisher An entity responsible for making the resource available Universidad Autónoma de Madrid Erasmus Research Institute of Management Erasmus University Rotterdam Date A point or period of time associated with an event in the lifecycle of the resource October 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/d7c41c9c741f701d8ed68b151593fb75.pdf 04aa260a3591409cc3f245f919d68fc3 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Zigzag Expanded Navigation Plots in R: The R Package zenplots Subject The topic of the resource : R, data visualization, data analysis, graphics, grid, loon. Description An account of the resource We describe the features and implementation of the R package zenplots (zigzag expanded navigation plots) for displaying high-dimensional data according to the recently proposed zenplots. By default, zenplots lay out alternating one- and two-dimensional plots in a zigzag-like pattern where adjacent axes share the same variate. Zenplots are especially useful when subsets of pairs can be identified as of particular interest by some measure, or as not meaningfully comparable, or when pairs of variates can be ordered in terms of potential interest to view, or the number of pairs is too large for more traditional layouts such as a scatterplot matrix. They also allow an essentially arbitrary layout of plots. A highdimensional space can be explored in a zenplot (zenplot()) by navigating through lower dimensional subspaces along a zenpath (zenpath()) which orders the dimensions (i.e., variates) visited according to some measure of interestingness; see Hofert and Oldford (2018) for an application to S&P 500 constituent data. The R package zenplots provides compact displays for high-dimensional data via the notion of zenplots, grouping of variates, and customizable displays of zigzag layouts. It accommodates different graphical systems including the base graphics package of R Core Team (2020b), the package grid of R Core Team (2020a) (and hence packages like ggplot2 of Wickham et al. 2020), and the interactive graphical package loon of Waddell and Oldford (2020). zenplots handles groups of variates, partial and fully missing data, and more. One important feature is that zenplot() and its auxiliary functions in zenplots distinguish layout from plotting which allows one to freely choose and create one- and twodimensional plot functions; predefined functions are exported for all graphical systems. All R plots in this paper are reproducible with the vignette "selected_features" (available in zenplots ≥ 0.0-2). Creator An entity primarily responsible for making the resource Marius Hofert Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i04 Publisher An entity responsible for making the resource available University of Waterloo Date A point or period of time associated with an event in the lifecycle of the resource October 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/b5d0e17abf30e0fa7c9586ecf4651170.pdf 4f931994a73be2cbe2baad8b708674ec 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Computationally Efficient Simulation of Queues: The R Package queuecomputer Subject The topic of the resource queues, queueing theory, discrete event simulation, operations research, approximate Bayesian computation, R Description An account of the resource Large networks of queueing systems model important real-world systems such as MapReduce clusters, web-servers, hospitals, call centers and airport passenger terminals. To model such systems accurately, we must infer queueing parameters from data. Unfortunately, for many queueing networks there is no clear way to proceed with parameter inference from data. Approximate Bayesian computation could offer a straightforward way to infer parameters for such networks if we could simulate data quickly enough. We present a computationally efficient method for simulating from a very general set of queueing networks with the R package queuecomputer. Remarkable speedups of more than 2 orders of magnitude are observed relative to the popular DES packages simmer and simpy. We replicate output from these packages to validate the package. The package is modular and integrates well with the popular R package dplyr. Complex queueing networks with tandem, parallel and fork/join topologies can easily be built with these two packages together. We show how to use this package with two examples: a call center and an airport terminal. Creator An entity primarily responsible for making the resource Anthony Ebert Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i05 Publisher An entity responsible for making the resource available Queensland University of Technology ACEMS Date A point or period of time associated with an event in the lifecycle of the resource October 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/09b4cc774fc89e4330454faffc742bbe.pdf 91b6e4ad72e5ad8faf797308ba93be7e 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Patch-Wise Adaptive Weights Smoothing in R Subject The topic of the resource image denoising, patch-wise structural adaptive smoothing, total variation, nonlocal means, R. Description An account of the resource Image reconstruction from noisy data has a long history of methodological development and is based on a variety of ideas. In this paper we introduce a new method called patchwise adaptive smoothing, that extends the propagation-separation approach by using comparisons of local patches of image intensities to define local adaptive weighting schemes for an improved balance of reduced variability and bias in the reconstruction result. We present the implementation of the new method in an R package aws and demonstrate its properties on a number of examples in comparison with other state-of-the art image reconstruction methods Creator An entity primarily responsible for making the resource Jörg Polzehl Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i06 Publisher An entity responsible for making the resource available Weierstrass Institute Date A point or period of time associated with an event in the lifecycle of the resource October 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/48309968289ad25a131d47616d1288a1.pdf f034654b185deaa45817e8a406e36d62 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference Subject The topic of the resource BUGS, parallel computing, Markov chain Monte Carlo, Gibbs sampling, Bayesian analysis, hierarchical models, directed acyclic graph. Description An account of the resource MultiBUGS is a new version of the general-purpose Bayesian modeling software BUGS that implements a generic algorithm for parallelizing Markov chain Monte Carlo (MCMC) algorithms to speed up posterior inference of Bayesian models. The algorithm parallelizes evaluation of the product-form likelihoods formed when a parameter has many children in the directed acyclic graph (DAG) representation; and parallelizes sampling of conditionally-independent sets of parameters. A heuristic algorithm is used to decide which approach to use for each parameter and to apportion computation across computational cores. This enables MultiBUGS to automatically parallelize the broad range of statistical models that can be fitted using BUGS-language software, making the dramatic speed-ups of modern multi-core computing accessible to applied statisticians, without requiring any experience of parallel programming. We demonstrate the use of MultiBUGS on simulated data designed to mimic a hierarchical e-health linked-data study of methadone prescriptions including 425,112 observations and 20,426 random effects. Posterior inference for the e-health model takes several hours in existing software, but MultiBUGS can perform inference in only 28 minutes using 48 computational cores. Creator An entity primarily responsible for making the resource Robert J. B. Goudie Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i07 Publisher An entity responsible for making the resource available University of Cambridge Date A point or period of time associated with an event in the lifecycle of the resource October 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/73e903443f727c9f5362180f5b53c981.pdf b2914d3db6fcf61f3363cc3a4a6a7477 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Phonetic Spelling Algorithm Implementations for R Subject The topic of the resource text processing, phonetics, linguistics, record linkage, demography, R. Description An account of the resource The phonics package provides several functions for indexing words by their English language pronunciation. Over nearly one hundred years, many different algorithms have been developed to support word and name indexing. From Soundex, developed in the early 20th century and predating the digital computer, through to modern digital phonetic algorithms like Phonex, the phonics package provides support for more than a dozen methods. Together, these provide phonetic algorithms appropriate for use in name indexing and name matching across a variety of English language use cases Creator An entity primarily responsible for making the resource James P. Howard, II Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i08 Publisher An entity responsible for making the resource available Johns Hopkins Applied Physics Laboratory Date A point or period of time associated with an event in the lifecycle of the resource October 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/68235015446dd0cb5f53b7f29014b08b.pdf 431fb112912173cb8ea3ef0e2e174d2d 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond Subject The topic of the resource hierarchical data, multiple imputation, multilevel models, measurement error, heaping, R Description An account of the resource Applications of multiple imputation have long outgrown the traditional context of dealing with item nonresponse in cross-sectional data sets. Nowadays multiple imputation is also applied to impute missing values in hierarchical data sets, address confidentiality concerns, combine data from different sources, or correct measurement errors in surveys. However, software developments did not keep up with these recent extensions. Most imputation software can only deal with item nonresponse in cross-sectional settings and extensions for hierarchical data – if available at all – are typically limited in scope. Furthermore, to our knowledge no software is currently available for dealing with measurement error using multiple imputation approaches. The R package hmi tries to close some of these gaps. It offers multiple imputation routines in hierarchical settings for many variable types (for example, nominal, ordinal, or continuous variables). It also provides imputation routines for interval data and handles a common measurement error problem in survey data: biased inferences due to implicit rounding of the reported values. The user-friendly setup which only requires the data and optionally the specification of the analysis model of interest makes the package especially attractive for users less familiar with the peculiarities of multiple imputation. The compatibility with the popular mice package (Van Buuren and Groothuis-Oudshoorn 2011) ensures that the rich set of analysis and diagnostic tools and post-imputation functions available in mice can be used easily, once the data have been imputed Creator An entity primarily responsible for making the resource Matthias Speidel Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i09 Publisher An entity responsible for making the resource available Institute for Employment Research Date A point or period of time associated with an event in the lifecycle of the resource October 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/d7856db2c1a51d7411f7281385f43d58.pdf 016dc2def49e7b84e816b7a549fb3863 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 95 Tahun 2020 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v095 Date A point or period of time associated with an event in the lifecycle of the resource 2020 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 Computing the Kolmogorov-Smirnov Distribution When the Underlying CDF is Purely Discrete, Mixed, or Continuous Subject The topic of the resource Kolmogorov-Smirnov test statistic, discontinuous (discrete or mixed) distribution, fast Fourier transform, double boundary non-crossing, rectangle probability for uniform order statistics Description An account of the resource The distribution of the Kolmogorov-Smirnov (KS) test statistic has been widely studied under the assumption that the underlying theoretical cumulative distribution function (CDF), F(x), is continuous. However, there are many real-life applications in which fitting discrete or mixed distributions is required. Nevertheless, due to inherent difficulties, the distribution of the KS statistic when F(x) has jump discontinuities has been studied to a much lesser extent and no exact and efficient computational methods have been proposed in the literature. In this paper, we provide a fast and accurate method to compute the (complementary) CDF of the KS statistic when F(x) is discontinuous, and thus obtain exact p values of the KS test. Our approach is to express the complementary CDF through the rectangle probability for uniform order statistics, and to compute it using fast Fourier transform (FFT). Secondly, we provide a C++ and an R implementation of the proposed method, which fills the existing gap in statistical software. We give also a useful extension of the Schmid’s asymptotic formula for the distribution of the KS statistic, relaxing his requirement for F(x) to be increasing between jumps and thus allowing for any general mixed or purely discrete F(x). The numerical performance of the proposed FFT-based method, implemented both in C++ and in the R package KSgeneral, available from https://CRAN.R-project.org/package=KSgeneral, is illustrated when F(x) is mixed, purely discrete, and continuous. The performance of the general asymptotic formula is also studied Creator An entity primarily responsible for making the resource Dimitrina S. Dimitrova Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v095i10 Publisher An entity responsible for making the resource available City, University of London Date A point or period of time associated with an event in the lifecycle of the resource October 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