1 10 15 https://repository.horizon.ac.id/files/original/684d676bb4709a11ae99f584a72fabfc.pdf 0b65dc32cf4408dd7fc33aca3cc24076 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Analysis of Multiplex Social Networks with R Subject The topic of the resource networks, multiplex, multilayer, social network analysis, R. Description An account of the resource Multiplex social networks are characterized by a common set of actors connected through multiple types of relations. The multinet package provides a set of R functions to analyze multiplex social networks within the more general framework of multilayer networks, where each type of relation is represented as a layer in the network. The package contains functions to import/export, create and manipulate multilayer networks, implementations of several state-of-the-art multiplex network analysis algorithms, e.g., for centrality measures, layer comparison, community detection and visualization. Internally, the package is mainly written in native C++ and integrated with R using the Rcpp package. Creator An entity primarily responsible for making the resource Matteo Magnani Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i08 Publisher An entity responsible for making the resource available InfoLab Uppsala University Date A point or period of time associated with an event in the lifecycle of the resource May 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/a34cceab26af7b451381e75986a4eef1.pdf 65ac448a40ecf8daecdfb08c421bae62 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Bayesian Multivariate Spatial Models for Lattice Data with INLA Subject The topic of the resource INLA, spatial statistics, multivariate modeling, R. Description An account of the resource The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with the INLA package for Bayesian inference. The multivariate spatial models implemented include different structures to model the spatial variation of the variables and the between-variables variability. In this way, fitting multivariate spatial models becomes faster and easier. The use of the different models included in the package is illustrated using two different datasets: the well-known North Carolina SIDS data and mortality by three causes of death in Comunidad Valenciana (Spain). Creator An entity primarily responsible for making the resource Francisco Palmí-Perales Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i02 Publisher An entity responsible for making the resource available Universidad de Castilla-La Mancha Date A point or period of time associated with an event in the lifecycle of the resource May 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/67297bfc5f31382d2c8551f9783e9ea9.pdf e3e26b0fc4055785d8b5ada40f9a4f26 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Conformal Prediction with Orange Subject The topic of the resource conformal prediction, nonconformity, machine learning, Python, Orange Description An account of the resource Conformal predictors estimate the reliability of outcomes made by supervised machine learning models. Instead of a point value, conformal prediction defines an outcome region that meets a user-specified reliability threshold. Provided that the data are independently and identically distributed, the user can control the level of the prediction errors and adjust it following the requirements of a given application. The quality of conformal predictions often depends on the choice of nonconformity estimate for a given machine learning method. To promote the selection of a successful approach, we have developed Orange3-Conformal, a Python library that provides a range of conformal prediction methods for classification and regression. The library also implements several nonconformity scores. It has a modular design and can be extended to add new conformal prediction methods and nonconformities Creator An entity primarily responsible for making the resource Tomaž Hočevar Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i07 Publisher An entity responsible for making the resource available University of Ljubljana Date A point or period of time associated with an event in the lifecycle of the resource May 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/3ba33f5118ff3ae4e293ab42a27963de.pdf 22a3dd80d641a669a382982867a4443c 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Continuous Time Individual-Level Models of Infectious Disease: Package EpiILMCT Subject The topic of the resource EpiILMCT, infectious disease, individual level modeling, spatial models, contact networks, R Description An account of the resource This paper describes the R package EpiILMCT, which allows users to study the spread of infectious disease using continuous time individual level models (ILMs). The package provides tools for simulation from continuous time ILMs that are based on either spatial demographic, contact network, or a combination of both of them, and for the graphical summarization of epidemics. Model fitting is carried out within a Bayesian Markov Chain Monte Carlo framework. The continuous time ILMs can be implemented within either susceptible-infected-removed (SIR) or susceptible-infected-notified-removed (SIN R) compartmental frameworks. As infectious disease data is often partially observed, data uncertainties in the form of missing infection times – and in some situations missing removal times – are accounted for using data augmentation techniques. The package is illustrated using both simulated and an experimental data set on the spread of the tomato spotted wilt virus disease Creator An entity primarily responsible for making the resource Waleed Almutiry Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i10 Publisher An entity responsible for making the resource available Qassim University Date A point or period of time associated with an event in the lifecycle of the resource May 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/6e2854df231ef231949b670d861d66f3.pdf e7c86e49b580e42ff951617a4f90a39d 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R Subject The topic of the resource optimal cutpoint, ROC curve, bootstrap, R. Description An account of the resource “Optimal cutpoints” for binary classification tasks are often established by testing which cutpoint yields the best discrimination, for example the Youden index, in a specific sample. This results in “optimal” cutpoints that are highly variable and systematically overestimate the out-of-sample performance. To address these concerns, the cutpointr package offers robust methods for estimating optimal cutpoints and the out-of-sample performance. The robust methods include bootstrapping and smoothing based on kernel estimation, generalized additive models, smoothing splines, and local regression. These methods can be applied to a wide range of binary-classification and cost-based metrics. cutpointr also provides mechanisms to utilize user-defined metrics and estimation methods. The package has capabilities for parallelization of the bootstrapping, including reproducible random number generation. Furthermore, it is pipe-friendly, for example for compatibility with functions from tidyverse. Various functions for plotting receiver operating characteristic curves, precision recall graphs, bootstrap results and other representations of the data are included. The package contains example data from a study on psychological characteristics and suicide attempts suitable for applying binary classification algorithms. Creator An entity primarily responsible for making the resource Christian Thiele Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i11 Publisher An entity responsible for making the resource available University of Applied Sciences Bielefeld Date A point or period of time associated with an event in the lifecycle of the resource May 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/a69bec8b00c875c300376224aefbd1fd.pdf b6626f12915a5554e41827d4b537ad0f 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Dimension Reduction for Time Series in a Blind Source Separation Context Using R Subject The topic of the resource blind source separation, supervised dimension reduction, R. Description An account of the resource Multivariate time series observations are increasingly common in multiple fields of science but the complex dependencies of such data often translate into intractable models with large number of parameters. An alternative is given by first reducing the dimension of the series and then modelling the resulting uncorrelated signals univariately, avoiding the need for any covariance parameters. A popular and effective framework for this is blind source separation. In this paper we review the dimension reduction tools for time series available in the R package tsBSS. These include methods for estimating the signal dimension of second-order stationary time series, dimension reduction techniques for stochastic volatility models and supervised dimension reduction tools for time series regression. Several examples are provided to illustrate the functionality of the package. 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/v098i15 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 May 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/8cc223f326844e261617f96994a532a6.pdf 01b2eb7fcc1bbbb8a12441bd9fcf77ce 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 FRK: An R Package for Spatial and Spatio-Temporal Prediction with Large Datasets Subject The topic of the resource : basic areal units, EM algorithm, fixed rank kriging, spatial random effects model, spatial prediction. Description An account of the resource FRK is an R software package for spatial/spatio-temporal modeling and prediction with large datasets. It facilitates optimal spatial prediction (kriging) on the most commonly used manifolds (in Euclidean space and on the surface of the sphere), for both spatial and spatio-temporal fields. It differs from many of the packages for spatial modeling and prediction by avoiding stationary and isotropic covariance and variogram models, instead constructing a spatial random effects (SRE) model on a fine-resolution discretized spatial domain. The discrete element is known as a basic areal unit (BAU), whose introduction in the software leads to several practical advantages. The software can be used to (i) integrate multiple observations with different supports with relative ease; (ii) obtain exact predictions at millions of prediction locations (without conditional simulation); and (iii) distinguish between measurement error and fine-scale variation at the resolution of the BAU, thereby allowing for reliable uncertainty quantification. The temporal component is included by adding another dimension. A key component of the SRE model is the specification of spatial or spatio-temporal basis functions; in the package, they can be generated automatically or by the user. The package also offers automatic BAU construction, an expectation-maximization (EM) algorithm for parameter estimation, and functionality for prediction over any user-specified polygons or BAUs. Use of the package is illustrated on several spatial and spatio-temporal datasets, and its predictions and the model it implements are extensively compared to others commonly used for spatial prediction and modeling Creator An entity primarily responsible for making the resource Andrew Zammit-Mangion Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i04 Publisher An entity responsible for making the resource available University of Wollongong Date A point or period of time associated with an event in the lifecycle of the resource May 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/34d9549854bf7b14fc1dd93dcfe83c4d.pdf ae4a9f869f2acdd517d834a64b5de41f 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R Subject The topic of the resource input-dependent noise, level-set estimation, optimization, replication, stochastic kriging Description An account of the resource An increasing number of time-consuming simulators exhibit a complex noise structure that depends on the inputs. For conducting studies with limited budgets of evaluations, new surrogate methods are required in order to simultaneously model the mean and variance fields. To this end, we present the hetGP package, implementing many recent advances in Gaussian process modeling with input-dependent noise. First, we describe a simple, yet efficient, joint modeling framework that relies on replication for both speed and accuracy. Then we tackle the issue of data acquisition leveraging replication and exploration in a sequential manner for various goals, such as for obtaining a globally accurate model, for optimization, or for contour finding. Reproducible illustrations are provided throughout. Creator An entity primarily responsible for making the resource Mickaël Binois Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i13 Publisher An entity responsible for making the resource available Argonne National Laboratory Date A point or period of time associated with an event in the lifecycle of the resource May 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/ee9901304824f3cd9ba1e2b418040ad4.pdf e110bab98d3d2e8978951f215877c1f8 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 mexhaz: An R Package for Fitting Flexible Hazard-Based Regression Models for Overall and Excess Mortality with a Random Effect Subject The topic of the resource adaptive Gauss-Hermite quadrature, excess hazard, flexible models, frailty models, time-dependent effects, C. Description An account of the resource We present mexhaz, an R package for fitting flexible hazard-based regression models with the possibility to add time-dependent effects of covariates and to account for a twolevel hierarchical structure in the data through the inclusion of a normally distributed random intercept (i.e., a log-normally distributed shared frailty). Moreover, mexhazbased models can be fitted within the excess hazard setting by allowing the specification of an expected hazard in the model. These models are of common use in the context of the analysis of population-based cancer registry data. Follow-up time can be entered in the right-censored or counting process input style, the latter allowing models with delayed entries. The logarithm of the baseline hazard can be flexibly modeled with B-splines or restricted cubic splines of time. Parameters estimation is based on likelihood maximization: in deriving the contribution of each observation to the cluster-specific conditional likelihood, Gauss-Legendre quadrature is used to calculate the cumulative hazard; the cluster-specific marginal likelihoods are then obtained by integrating over the random effects distribution, using adaptive Gauss-Hermite quadrature. Functions to compute and plot the predicted (excess) hazard and (net) survival (possibly with cluster-specific predictions in the case of random effect models) are provided. We illustrate the use of the different options of the mexhaz package and compare the results obtained with those of other available R packages. Creator An entity primarily responsible for making the resource Hadrien Charvat Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i14 Publisher An entity responsible for making the resource available National Cancer Center Japan Date A point or period of time associated with an event in the lifecycle of the resource May 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/4ef3f34f887161406e18a25d18520f78.pdf b0658c2be348b72112469720b0fa9205 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 98 Tahun 2021 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v098 Date A point or period of time associated with an event in the lifecycle of the resource 2021 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 Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package Subject The topic of the resource model-based clustering, classification, discriminant analysis, EM algorithm, generalized hyperbolic distribution Description An account of the resource The MixGHD package for R performs model-based clustering, classification, and discriminant analysis using the generalized hyperbolic distribution (GHD). This approach is suitable for data that can be considered a realization of a (multivariate) continuous random variable. The GHD has the advantage of being flexible due to skewness, concentration, and index parameters; as such, clustering methods that use this distribution are capable of estimating clusters characterized by different shapes. The package provides five different models all based on the GHD, an efficient routine for discriminant analysis, and a function to measure cluster agreement. This paper is split into three parts: the first is devoted to the formulation of each method, extending them for classification and discriminant analysis applications, the second focuses on the algorithms, and the third shows the use of the package on real datasets. Creator An entity primarily responsible for making the resource Cristina Tortora Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v098i03 Publisher An entity responsible for making the resource available MacEwan University Date A point or period of time associated with an event in the lifecycle of the resource May 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