Volume 101 Tahun 2022
Dublin Core
Title
Volume 101 Tahun 2022
Source
https://www.jstatsoft.org/issue/view/v101
Date
2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Collection Items
The poolr Package for Combining Independent and Dependent p Values
The poolr package provides an implementation of a variety of methods for pooling
(i.e., combining) p values, including Fisher’s method, Stouffer’s method, the inverse chisquare method, the binomial test, the Bonferroni method, and Tippett’s method.…
(i.e., combining) p values, including Fisher’s method, Stouffer’s method, the inverse chisquare method, the binomial test, the Bonferroni method, and Tippett’s method.…
lpdensity: Local Polynomial Density Estimation and Inference
Density estimation and inference methods are widely used in empirical work. When
the underlying distribution has compact support, conventional kernel-based density estimators are no longer consistent near or at the boundary because of their…
the underlying distribution has compact support, conventional kernel-based density estimators are no longer consistent near or at the boundary because of their…
Fast Kernel Smoothing in R with Applications to Projection Pursuit
This paper introduces the R package FKSUM, which offers fast and exact evaluation of
univariate kernel smoothers. The main kernel computations are implemented in C++, and
are wrapped in simple, intuitive and versatile R functions. The fast kernel…
univariate kernel smoothers. The main kernel computations are implemented in C++, and
are wrapped in simple, intuitive and versatile R functions. The fast kernel…
tlrmvnmvt: Computing High-Dimensional Multivariate Normal and Student-t Probabilities with Low-Rank Methods in R
This paper introduces the usage and performance of the R package tlrmvnmvt, aimed
at computing high-dimensional multivariate normal and Student-t probabilities. The
package implements the tile-low-rank methods with block reordering and the…
at computing high-dimensional multivariate normal and Student-t probabilities. The
package implements the tile-low-rank methods with block reordering and the…
bbl: Boltzmann Bayes Learner for High-Dimensional Inference with Discrete Predictors in R
Jun Woo, Jinhua Wang
Non-regression-based inferences, such as discriminant analysis, can account for the
effect of predictor distributions that may be significant in big data modeling. We describe bbl, an R package for Boltzmann Bayes learning, which enables a…
effect of predictor distributions that may be significant in big data modeling. We describe bbl, an R package for Boltzmann Bayes learning, which enables a…
The JuliaConnectoR: A Functionally-Oriented Interface for Integrating Julia in R
Like many groups considering the new programming language Julia, we faced the
challenge of accessing the algorithms that we develop in Julia from R. Therefore, we
developed the R package JuliaConnectoR, available from the Comprehensive R…
challenge of accessing the algorithms that we develop in Julia from R. Therefore, we
developed the R package JuliaConnectoR, available from the Comprehensive R…
tidypaleo: Visualizing Paleoenvironmental Archives Using ggplot2
This paper presents the tidypaleo package for R, which enables high-quality reproducible visualizations of time-stratigraphic multivariate data that is common to several
disciplines of the natural sciences. Rather than introduce new plotting…
disciplines of the natural sciences. Rather than introduce new plotting…
nference Tools for Markov Random Fields on Lattices: The R Package mrf2d
Markov random fields on two-dimensional lattices are behind many image analysis
methodologies. mrf2d provides tools for statistical inference on a class of discrete stationary Markov random field models with pairwise interaction, which includes many…
methodologies. mrf2d provides tools for statistical inference on a class of discrete stationary Markov random field models with pairwise interaction, which includes many…
TransModel: An R Package for Linear Transformation Model with Censored Data
Linear transformation models, including the proportional hazards model and proportional odds model, under right censoring were discussed by Chen, Jin, and Ying (2002).
The asymptotic variance of the estimator they proposed has a closed form and can…
The asymptotic variance of the estimator they proposed has a closed form and can…
Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data
We describe a new algorithm and R package for peak detection in genomic data sets
using constrained changepoint models. These detect changes from background to peak
regions by imposing the constraint that the mean should alternately increase then…
using constrained changepoint models. These detect changes from background to peak
regions by imposing the constraint that the mean should alternately increase then…