Numerical Analysis and Scientific Computing Commons^™

Rcosmo: R Package For Analysis Of Spherical, Healpix And Cosmological Data, Daniel Fryer, Ming Li, Andriy Olenko

The R Journal

The analysis of spatial observations on a sphere is important in areas such as geosciences, physics and embryo research, just to name a few. The purpose of the package rcosmo is to conduct efficient information processing, visualisation, manipulation and spatial statistical analysis of Cosmic Microwave Background (CMB) radiation and other spherical data. The package was developed for spherical data stored in the Hierarchical Equal Area isoLatitude Pixelation (Healpix) representation. rcosmo has more than 100 different functions. Most of them initially were developed for CMB, but also can be used for other spherical data as rcosmo contains tools for transforming spherical …

Lspartition: Partitioning-Based Least Squares Regression, Matias D. Cattaneo, Max H. Farrell, Yingjie Feng

The R Journal

Nonparametric partitioning-based least squares regression is an important tool in empirical work. Common examples include regressions based on splines, wavelets, and piecewise polynomials. This article discusses the main methodological and numerical features of the R software package lspartition, which implements results for partitioning-based least squares (series) regression estimation and inference from Cattaneo and Farrell (2013) and Cattaneo, Farrell, and Feng (2020). These results cover the multivariate regression function as well as its derivatives. First, the package provides data-driven methods to choose the number of partition knots optimally, according to integrated mean squared error, yielding optimal point estimation. Second, robust …

Mudfold: An R Package For Nonparametric Irt Modelling Of Unfolding Processes, Spyros E. Balafas, Wim P. Krijnen, Wendy J. Post, Ernst C. Wit

The R Journal

Item response theory (IRT) models for unfolding processes use the responses of individuals to attitudinal tests or questionnaires in order to infer item and person parameters located on a latent continuum. Parametric models in this class use parametric functions to model the response process, which in practice can be restrictive. MUDFOLD (Multiple UniDimensional unFOLDing) can be used to obtain estimates of person and item ranks without imposing strict parametric assumptions on the item response functions (IRFs). This paper describes the implementation of the MUDFOLD method for binary preferential-choice data in the R package mudfold. The latter incorporates estimation, visualization, …

Mapping Smoothed Spatial Effect Estimates From Individual-Level Data: Mapgam, Lu Bai, Daniel L. Gillen, Scott M. Bartell, Verónica M. Vieira

The R Journal

We introduce and illustrate the utility of MapGAM, a user-friendly R package that provides a unified framework for estimating, predicting and drawing inference on covariate-adjusted spatial effects using individual-level data. The package also facilitates visualization of spatial effects via automated mapping procedures. MapGAM estimates covariate-adjusted spatial associations with a univariate or survival outcome using generalized additive models that include a non-parametric bivariate smooth term of geolocation parameters. Estimation and mapping methods are implemented for continuous, discrete, and right-censored survival data. In the current manuscript, we summarize the methodology implemented in MapGAM and illustrate the package using two example simulated …

Nlints: An R Package For Causality Detection In Time Series, Youssef Hmamouche

The R Journal

The causality is an important concept that is widely studied in the literature, and has several applications, especially when modelling dependencies within complex data, such as multivariate time series. In this article, we present a theoretical description of methods from the NlinTS package, and we focus on causality measures. The package contains the classical Granger causality test. To handle non-linear time series, we propose an extension of this test using an artificial neural network. The package includes an implementation of the Transfer entropy, which is also considered as a non linear causality measure based on information theory. For discrete variables, …

Editorial, Michael J. Kane

The R Journal

Onbehalf of the editorial board, I am pleased to present Volume 12, Issue 1 of the R Journal and mysecond issue as the Editor in Chief. Since the last issue Simon Urbanek has joined the editorial board and we have made a few structural changes. First, the R Foundation has approved the R Journal having Associate Editors. This change will allow us to address the increase in submission volume. The addition of the new AE positions should help alleviate some of the workload the editors have been dealing with and will result in shorter turn-around times for submissions. Second, complete …

Gk: An R Package For The G-And-K And Generalised G-And-H Distributions, Dennis Prangle

The R Journal

The g-and-k and (generalised) g-and-h distributions are flexible univariate distributions which can model highly skewed or heavy tailed data through only four parameters: location and scale, and two shape parameters influencing the skewness and kurtosis. These distributions have the unusual property that they are defined through their quantile function (inverse cumulative distribution function) and their density is unavailable in closed form, which makes parameter inference complicated. This paper presents the gk R package to work with these distributions. It provides the usual distribution functions and several algorithms for inference of independent identically distributed data, including the finite difference stochastic approximation …

Similar: R Code Clone And Plagiarism Detection, Maciej Bartoszuk, Marek Gagolewski

The R Journal

Third-party software for assuring source code quality is becoming increasingly popular. Tools that evaluate the coverage of unit tests, perform static code analysis, or inspect run-time memory use are crucial in the software development life cycle. More sophisticated methods allow for performing meta-analyses of large software repositories, e.g., to discover abstract topics they relate to or common design patterns applied by their developers. They may be useful in gaining a better understanding of the component interdependencies, avoiding cloned code as well as detecting plagiarism in programming classes.

Ameaningful measure of similarity of computer programs often forms the basis of such …

Coxphlb: An R Package For Analyzing Length Biased Data Under Cox Model, Chi Hyun Lee, Heng Zhou, Jing Ning, Diane D. Liu, Yu Shen

The R Journal

Data subject to length-biased sampling are frequently encountered in various applications including prevalent cohort studies and are considered as a special case of left-truncated data under the stationarity assumption. Many semiparametric regression methods have been proposed for length biased data to model the association between covariates and the survival outcome of interest. In this paper, we present a brief review of the statistical methodologies established for the analysis of length-biased data under the Cox model, which is the most commonly adopted semiparametric model, and introduce an R package CoxPhLb that implements these methods. Specifically, the package includes features such as …

The R Package Nonprobest For Estimation In Non-Probability Surveys, M. Rueda, R. Ferri-García, L. Castro

The R Journal

Different inference procedures are proposed in the literature to correct selection bias that might be introduced with non-random sampling mechanisms. The R package NonProbEst enables the estimation of parameters using some of these techniques to correct selection bias in non-probability surveys. The mean and the total of the target variable are estimated using Propensity Score Adjustment, calibration, statistical matching, model-based, model-assisted and model-calibratated techniques. Confidence intervals can also obtained for each method. Machine learning algorithms can be used for estimating the propensities or for predicting the unknown values of the target variable for the non-sampled units. Variance of a given …

Variable Importance Plots: An Introduction To The Vip Package, Brandon M. Bartoszuk, Marek Gagolewski

The R Journal

In the era of “big data”, it is becoming more of a challenge to not only build state-of-the-art predictive models, but also gain an understanding of what’s really going on in the data. For example, it is often of interest to know which, if any, of the predictors in a fitted model are relatively influential on the predicted outcome. Some modern algorithms—like random forests (RFs) and gradient boosted decision trees (GBMs)—have a natural way of quantifying the importance or relative influence of each feature. Other algorithms—like naive Bayes classifiers and support vector machines—are not capable of doing so and model-agnostic …

Tsmp: An R Package For Time Series With Matrix Profile, Francisco Bischoff, Pedro Pereira Rodriques

The R Journal

This article describes tsmp, an R package that implements the MP concept for TS. The tsmp package is a toolkit that allows all-pairs similarity joins, motif, discords and chains discovery, semantic segmentation, etc. Here we describe how the tsmp package may be used by showing some of the use-cases from the original articles and evaluate the algorithm speed in the R environment. This package can be downloaded at https://CRAN.R-project.org/package=tsmp.

R Foundation News, Torsten Hothorn

The R Journal

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Projectmanagement: An R Package For Managing Projects, Juan Carlos Gonçalves-Dosantos, Ignacio García-Jurado, Julián Costa

The R Journal

Project management is an important body of knowledge and practices that comprises the planning, organisation and control of resources to achieve one or more pre-determined objectives. In this paper, we introduce ProjectManagement, a new R package that provides the necessary tools to manage projects in a broad sense, and illustrate its use by examples.

Npordtests: An R Package Of Nonparametric Tests For Equality Of Location Against Ordered Alternatives, Bulent Altunkaynak, Hamza Gamgam

The R Journal

Ordered alternatives are an important statistical problem in many situation such as increased risk of congenital malformation caused by excessive alcohol consumption during pregnancy life test experiments, drug-screening studies, dose-finding studies, the dose-response studies, age-related response. There are numerous other examples of this nature. In this paper, we present the npordtests package to test the equality of locations for ordered alternatives. The package includes the Jonckheere Terpstra, Beier and Buning’s Adaptive, Modified Jonckheere-Terpstra, Terpstra-Magel, Ferdhiana Terpstra-Magel, KTP, S and Gaur’s Gc tests. A simulation study is conducted to determine which test is the most appropriate test for which scenario and …

Spinifex: An R Package For Creating A Manual Tour Of Low-Dimensional Projections Of Multivariate Data, Nicholas Spyrison, Dianne Cook

The R Journal

Dynamic low-dimensional linear projections of multivariate data collectively known as tours provide an important tool for exploring multivariate data and models. The R package tourr provides functions for several types of tours: grand, guided, little, local and frozen. Each of these can be viewed dynamically, or saved into a data object for animation. This paper describes a new package, spinifex, which provides a manual tour of multivariate data where the projection coefficient of a single variable is controlled. The variable is rotated fully into the projection, or completely out of the projection. The resulting sequence of projections can be …

Mistr: A Computational Framework For Mixture And Composite Distributions, Lukas Sablica, Kurt Hornik

The R Journal

No abstract provided.

Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis

The R Journal

In the past 8 months, 1554 new packages were added to the CRAN package repository. 96 packages were unarchived and 843 were archived. The following shows the growth of the number of active packages in the CRAN package repository:

Skew-T Expected Information Matrix Evaluation And Use For Standard Error Calculations, R. Douglas Martin, Chindhanai Uthaisaad, Daniel Z. Xia

The R Journal

Skew-t distributions derived from skew-normal distributions, as developed by Azzalini and several co-workers, are popular because of their theoretical foundation and the availability of computational methods in the R package sn. One difficulty with this skew-t family is that the elements of the expected information matrix do not have closed form analytic formulas. Thus, we developed a numerical integration method of computing the expected information matrix in the R package skewtInfo. The accuracy of our expected information matrix calculation method was confirmed by comparing the result with that obtained using an observed information matrix for a very large sample …

Tools For Analyzing R Code The Tidy Way, Lucy D'Agostino Mcgowan, Sean Kross, Jeffrey Leek

The R Journal

With the current emphasis on reproducibility and replicability, there is an increasing need to examine how data analyses are conducted. In order to analyze the between researcher variability in data analysis choices as well as the aspects within the data analysis pipeline that contribute to the variability in results, we have created two R packages: matahari and tidycode. These packages build on methods created for natural language processing; rather than allowing for the processing of natural language, we focus on R code as the substrate of interest. The matahari package facilitates the logging of everything that is typed in the …