Numerical Analysis and Scientific Computing Commons^™

Hdm: High-Dimensional Metrics, Victor Chernozhukov, Chris Hansen, Martin Spindler

The R Journal

In this article the package High-dimensional Metrics hdm is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or policy variable) in a high-dimensional approximately sparse regression model, for average treatment effect (ATE) and average treatment effect for the treated (ATET), as well for extensions of these param eters to the endogenous setting are provided. Theory …

Distance Measures For Time Series In R: The Tsdist Package, Usue Mori, Alexander Mendiburu, Jose A. Lozano

The R Journal

The definition of a distance measure between time series is crucial for many time series data mining tasks, such as clustering and classification. For this reason, a vast portfolio of time series distance measures has been published in the past few years. In this paper, the TSdist package is presented, a complete tool which provides a unified framework to calculate the largest variety of time series dissimilarity measures available in R at the moment, to the best of our knowledge. The package implements some popular distance measures which were not previously available in R, and moreover, it also provides wrappers …

Condsurv: An R Package For The Estimation Of The Conditional Survival Function For Ordered Multivariate Failure Time Data, Luis Meira-Machado, Meira-Machado Sestelo

The R Journal

One major goal in clinical applications of time-to-event data is the estimation of survival with censored data. The usual nonparametric estimator of the survival function is the time-honored Kaplan-Meier product-limit estimator. Though this estimator has been implemented in several R packages, the development of the condSURV R package has been motivated by recent contributions that allow the estimation of the survival function for ordered multivariate failure time data. The condSURV package provides three different approaches all based on the Kaplan-Meier estimator. In one of these approaches these quantities are estimated conditionally on current or past covariate measures. Illustration of the …

Measurement Units In R, Edzer Pebesma, Thomas Mailund, James Hiebert

The R Journal

We briefly review SI units, and discuss R packages that deal with measurement units, their compatibility and conversion. Built upon udunits2 and the UNIDATA udunits library, we introduce the package units that provides a class for maintaining unit metadata. When used in expression, it automatically converts units, and simplifies units of results when possible; in case of incompatible units, errors are raised. The class flexibly allows expansion beyond predefined units. Using units may eliminate a whole class of potential scientific programming mistakes. We discuss the potential and limitations of computing with explicit units.

Tigris: An R Package To Access And Work With Geographic Data From The Us Census Bureau, Kyle Walker

The R Journal

TIGER/Line shapefiles from the United States Census Bureau are commonly used for the mapping and analysis of US demographic trends. The tigris package provides a uniform interface for R users to download and work with these shapefiles. Functions in tigris allow R users to request Census geographic datasets using familiar geographic identifiers and return those datasets as objects of class "Spatial*DataFrame". In turn, tigris ensures consistent and high-quality spatial data for R users’ cartographic and spatial analysis projects that involve US Census data. This article provides an overview of the functionality of the tigris package, and concludes with an applied …

Mixtox: An R Package For Mixture Toxicity Assessment, Xiang-Wei Zhu, Jian-Yi Chen

The R Journal

Mixture toxicity assessment is indeed necessary for humans and ecosystems that are continually exposed to a variety of chemical mixtures. This paper describes an R package, called mixtox, which offers a general framework of curve fitting, mixture experimental design, and mixture toxicity prediction for practitioners in toxicology. The unique features of mixtox include: (1) constructing a uniform table for mixture experimental design; and (2) predicting toxicity of a mixture with multiple components based on reference models such as concentration addition, independent action, and generalized concentration addition. We describe the various functions of the package and provide examples to illustrate their …

Water: Tools And Functions To Estimate Actual Evapotranspiration Using Land Surface Energy Balance Models In R, Guillermo Federico Olmedo, Samuel Ortega-Farías, Daniel De La Fuente-Sáiz, David Fonseca- Luego, Fernando Fuentes-Peñailillo

The R Journal

The crop water requirement is a key factor in the agricultural process. It is usually estimated throughout actual evapotranspiration (ETa). This parameter is the key to develop irrigation strategies, to improve water use efficiency and to understand hydrological, climatic, and ecosystem processes. Currently, it is calculated with classical methods, which are difficult to extrapolate, or with land surface energy balance models (LSEB), such as METRIC and SEBAL, which are based on remote sensing data. This paper describes water, an open implementation of LSEB. The package provides several functions to estimate the parameters of the LSEB equation from satellite data …

A Parallel 3d Phase-Field Simulation Of Multi-Grain Growth Based On The Full Thread Tree, Ya-Jun Yin, Min Wang, Jian-Xin Zhou, Dun-Ming Liao, Xu Shen, Tao Chen

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.1 patched

CHANGES IN R 3.3.1

CHANGES IN R 3.3.0

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

In the past 8 months,1322 new packages were added to the CRAN package repository. 43 packages were unarchived,48 archived,1 package had to be removed.The following shows the growth of the number of active packages in the CRAN package repository:

Nonparametric Tests For The Interaction In Two-Way Factorial Designs Using R, Jos Feys

The R Journal

An increasing number of R packages include nonparametric tests for the interaction in two-way factorial designs. This paper briefly describes the different methods of testing and reports the resulting p-values of such tests on datasets for four types of designs: between, within, mixed, and pretest-posttest designs. Potential users are advised only to apply tests they are quite familiar with and not be guided by p-values for selecting packages and tests.

Using Decipher V2.0 To Analyze Big Biological Sequence Data In R, Erik S. Wright

The R Journal

In recent years, the cost of DNA sequencing has decreased at a rate that has outpaced improvements in memory capacity. It is now common to collect or have access to many gigabytes of biological sequences. This has created an urgent need for approaches that analyze sequences in subsets without requiring all of the sequences to be loaded into memory at one time. It has also opened opportunities to improve the organization and accessibility of information acquired in sequencing projects. The DECIPHER package offers solutions to these problems by assisting in the curation of large sets of biological sequences stored in …

Scmamp: Statistical Comparison Of Multiple Algorithms In Multiple Problems, Borja Calvo, Guzmán Santafé

The R Journal

Comparing the results obtained by two or more algorithms in a set of problems is a central task in areas such as machine learning or optimization. Drawing conclusions from these comparisons may require the use of statistical tools such as hypothesis testing. There are some interesting papers that cover this topic. In this manuscript we present scmamp, an R package aimed at being a tool that simplifies the whole process of analyzing the results obtained when comparing algorithms, from loading the data to the production of plots and tables.

Comparing the performance of different algorithms is an essential step …

Swmpr: An R Package For Retrieving, Organizing, And Analyzing Environmental Data For Estuaries, Marcus W. Beck

The R Journal

The System-Wide Monitoring Program (SWMP)was implemented in 1995 by the US National Estuarine Research Reserve System. This program has provided two decades of continuous monitoring data at over 140 fixed stations in 28 estuaries. However, the increasing quantity of data provided by the monitoring network has complicated broad-scale comparisons between systems and, in some cases, prevented simple trend analysis of water quality parameters at individual sites. This article describes the SWMPr package that provides several functions that facilitate data retrieval, organization, and analysis of time series data in the reserve estuaries. Previously unavailable functions for estuaries are also provided to …

Spatio-Temporal Interpolation Using Gstat, Benedikt Gräler, Edzer Pebesma, Gerard Heuvelink

The R Journal

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. Inareal-world application we comparespatio temporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the …

Model Builder For Item Factor Analysis With Openmx, Joshua N. Pritikin, Karen M. Schmidt

The R Journal

We introduce a shiny web application to facilitate the construction of Item Factor Analysis (a.k.a. Item Response Theory) models using the OpenMx package. The web application assists with importing data, outcome recoding, and model specification. However, the app does not conduct any analysis but, rather, generates an analysis script. Generated Rmarkdown output serves dual purposes: to analyze a data set and demonstrate good programming practices. The app can be used as a teaching tool or as a starting point for custom analysis scripts.

Quickpsy: An R Package To Fit Psychometric Functions For Multiple Groups, Daniel Linares, Joan López-Moliner

The R Journal

quickpsy is a package to parametrically fit psychometric functions. In comparison with previous R packages, quickpsy was built to easily fit and plot data for multiple groups. Here, we describe the standard parametric model used to fit psychometric functions and the standard estimation of its parameters using maximum likelihood. We also provide examples of usage of quickpsy, including how allowing the lapse rate to vary can sometimes eliminate the bias in parameter estimation, but not in general. Finally, we describe some implementation details, such as how to avoid the problems associated to round-off errors in the maximisation of the …

Variable Clustering In High-Dimensional Linear Regression: The R Package Clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, Mickael Canouil

The R Journal

Dimension reduction is one of the biggest challenges in high-dimensional regression models. We recently introduced a new methodology based on variable clustering as a means to reduce dimensionality. We present here the R package clere that implements some refinements of this methodology. An overview of the package functionalities as well as examples to run an analysis are described. Numerical experiments on real data were performed to illustrate the good predictive performance of our parsimonious method compared to standard dimension reduction approaches.

Maps, Coordinate Reference Systems And Visualising Geographic Data With Mapmisc, Patrick E. Brown

The R Journal

The mapmisc package provides functions for visualising geospatial data, including fetching background map layers, producing colour scales and legends, and adding scale bars and orientation arrows to plots. Background maps are returned in the coordinate reference system of the dataset supplied, and inset maps and direction arrows reflect the map projection being plotted. This is a “light weight” package having an emphasis on simplicity and ease of use

Editorial, Michael Lawrence

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 8, Issue 1 of the R Journal. This issue contains 27 contributed research articles. Each of them either presents an R package, a specific extension of an R package or applications using R packages available from the Comprehensive R Archive Network (CRAN, http:://CRAN.R-project.org). It thus provides a small but current cross-section of the burgeoning R ecosystem.

Metaplus: An R Package For The Analysis Of Robust Meta-Analysis And Meta-Regression, Ken J. Beath

The R Journal

The metaplus package is described with examples of its use for fitting meta-analysis and meta-regression. For either meta-analysis or meta-regression it is possible to fit one of three models: standard normal random effect, t-distribution random effect or mixture of normal random effects. The latter two models allow for robustness by allowing for a random effect distribution with heavier tails than the normal distribution, and for both robust models the presence of outliers may be tested using the parametric bootstrap. For the mixture of normal random effects model the outlier studies may be identified through their posterior probability of membership in …

Conditional Fractional Gaussian Fields With The Package Fieldsim, Alexandre Brouste, Jacques Istas, Sophie Lambert-Lacroix

The R Journal

We propose an effective and fast method to simulate multidimensional conditional fractional Gaussian fields with the package FieldSim. Our method is valid not only for conditional simulations associated to fractional Brownian fields, but to any Gaussian field and on any (non regular) grid of points.

Progenyclust: An R Package For Progeny Clustering, Chenyue W. Hu, Amina A. Qutub

The R Journal

Identifying the optimal number of clusters is a common problem faced by data scientists in various research fields and industry applications. Though many clustering evaluation techniques have been developed to solve this problem, the recently developed algorithm Progeny Clustering is a much faster alternative and one that is relevant to biomedical applications. In this paper, we introduce an R package progenyClust that implements and extends the original Progeny Clustering algorithm for evaluating clustering stability and identifying the optimal cluster number. We illustrate its applicability using two examples: a simulated test dataset for proof-of-concept, and a cell imaging dataset for demonstrating …

Statmod: Probability Calculations For The Inverse Gaussian Distribution, Göknur Giner, Gordon K. Smyth

The R Journal

The inverse Gaussian distribution (IGD) is a well known and often used probability distribution for which fully reliable numerical algorithms have not been available. We develop fast, reliable basic probability functions (dinvgauss, pinvgauss, qinvgauss and rinvgauss) for the IGD that work for all possible parameter values and which achieve close to full machine accuracy. The most challenging task is to compute quantiles for given cumulative probabilities and we develop a simple but elegant mathematical solution to this problem. We show that Newton’s method for finding the quantiles of a IGD always converges monotonically when started from the mode of the …

Heteroscedastic Censored And Truncated Regression With Crch, Jakob W. Messner, Georg J. Mayr, Achim Zeileis

The R Journal

The crch package provides functions for maximum likelihood estimation of censored or truncated regression models with conditional heteroscedasticity along with suitable standard methods to summarize the fitted models and compute predictions, residuals, etc. The supported distributions include left- or right-censored or truncated Gaussian, logistic, or student-t distributions with potentially different sets of regressors for modeling the conditional location and scale. The models and their R implementation are introduced and illustrated by numerical weather prediction tasks using precipitation data for Innsbruck (Austria).

Stylometry With R: A Package For Computational Text Analysis, Maciej Eder, Jan Rybicki, Mike Kestemont

The R Journal

This software paper describes ‘Stylometry with R’ (stylo), a flexible R package for the high level analysis of writing style in stylometry. Stylometry (computational stylistics) is concerned with the quantitative study of writing style, e.g. authorship verification, an application which has considerable potential in forensic contexts, as well as historical research. In this paper we introduce the possibilities of stylo for computational text analysis, via a number of dummy case studies from English and French literature. We demonstrate how the package is particularly useful in the exploratory statistical analysis of texts, e.g. with respect to authorial writing style. …

Sbtools: A Package Connecting R To Cloud-Based Data For Collaborative Online Research, Luke A. Winslow, Scott Chamberlain, Alison P. Appling, Jordan S. Read

The R Journal

The adoption of high-quality tools for collaboration and reproducibile research such as R and Github is becoming more common in many research fields. While Github and other version management systems are excellent resources, they were originally designed to handle code and scale poorly to large text-based or binary datasets. A number of scientific data repositories are coming online and are often focused on dataset archival and publication. To handle collaborative workflows using large scientific datasets, there is increasing need to connect cloud-based online data storage to R. In this article, we describe how the new R package sbtools enables direct …

Mclust 5: Clustering, Classification And Density Estimation Using Gaussian Finite Mixture Models, Luca Scrucca, Michael Fop, T Brendan Murphy, Adrian E. Raftery

The R Journal

Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. mclust is a powerful and popular package which allows modelling of data as a Gaussian finite mixture with different covariance structures and different numbers of mixture components, for a variety of purposes of analysis. Recently, version 5 of the package has been made available on CRAN.This updated version adds new covariance structures, dimension reduction capabilities for visualisation, model selection criteria, initialisation strategies for the EM algorithm, and bootstrap-based inference, making it a full-featured R package for data analysis via …

Gender Prediction Methods Based On First Names With Genderizer, Kamil Wais

The R Journal

In recent years, there has been increased interest in methods for gender prediction based on f irst names that employ various open data sources. These methods have applications from bibliometric studies to customizing commercial offers for web users. Analysis of gender disparities in science based on such methods are published in the most prestigious journals, although they could be improved by choosing the most suited prediction method with optimal parameters and performing validation studies using the best data source for a given purpose. There is also a need to monitor and report how well a given prediction method works in …

Cryptrndtest: An R Package For Testing The Cryptographic Randomness, Haydar Demirhan, Nihan Bitirim

The R Journal

n this article, we introduce the R package CryptRndTest that performs eight statistical randomness tests on cryptographic random number sequences. The purpose of the package is to provide software implementing recently proposed cryptographic randomness tests utilizing goodness of-fit tests superior to the usual chi-square test in terms of statistical performance. Most of the tests included in package CryptRndTest are not available in other software packages such as the R package RDieHarder or the C library TestU01. Chi-square, Anderson-Darling, Kolmogorov-Smirnov, and Jarque-Bera goodness-of-fit procedures are provided along with cryptographic randomness tests. CryptRndTest utilizes multiple precision floating numbers for sequences longer than …