Numerical Analysis and Scientific Computing Commons^™

Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Air Force Institute Of Technology, Cade M. Saie, Trevor J. Bihl

The R Journal

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. …

The Welchadf Package For Robust Hypothesis Testing In Unbalanced Multivariate Mixed Models With Heteroscedastic And Non-Normal Data, Pablo J. Villacorta

The R Journal

A new R package is presented for dealing with non-normality and variance heterogeneity of sample data when conducting hypothesis tests of main effects and interactions in mixed models. The proposal departs from an existing SAS program which implements Johansen’s general formulation of Welch-James’s statistic with approximate degrees of freedom, which makes it suitable for testing any linear hypothesis concerning cell means in univariate and multivariate mixed model designs when the data pose non-normality and non-homogeneous variance. Improved type I error rate control is obtained using bootstrapping for calculating an empirical critical value, whereas robustness against non-normality is achieved through trimmed …

Mle.Tools: An R Package For Maximum Likelihood Bias Correction, Josmar Mazucheli, André Felipe B. Menezes, Saralees Nadarajah

The R Journal

Recently, Mazucheli (2017) uploaded the package mle.tools to CRAN. It can be used for bias corrections of maximum likelihood estimates through the methodology proposed by Cox and Snell (1968). The main function of the package, coxsnell.bc(), computes the bias corrected maximum likelihood estimates. Although in general, the bias corrected estimators may be expected to have better sampling properties than the uncorrected estimators, analytical expressions from the formula proposed by Cox and Snell (1968) are either tedious or impossible to obtain. The purpose of this paper is twofolded: to introduce the mle.tools package, especially the coxsnell.bc() function; secondly, to compare, for …

Liureg: A Comprehensive R Package For The Liu Estimation Of Linear Regression Model With Collinear Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf

The R Journal

The Liu regression estimator is now a commonly used alternative to the conventional ordinary least squares estimator that avoids the adverse effects in the situations when there exists a considerable degree of multicollinearity among the regressors. There are only a few software packages available for estimation of the Liu regression coefficients, though with limited methods to estimate the Liu biasing parameter without addressing testing procedures. Our liureg package can be used to estimate the Liu regression coefficients utilizing a range of different existing biasing parameters, to test these coefficients with more than 15 Liu related statistics, and to present different …

Ider: Intrinsic Dimension Estimation With R, Hideitsu Hino

The R Journal

In many data analyses, the dimensionality of the observed data is high while its intrinsic dimension remains quite low. Estimating the intrinsic dimension of an observed dataset is an essential preliminary step for dimensionality reduction, manifold learning, and visualization. This paper introduces an R package, named ider, that implements eight intrinsic dimension estimation methods, including a recently proposed method based on a second-order expansion of a probability mass function and a generalized linear model. The usage of each function in the package is explained with datasets generated using a function that is also included in the package

Carx: An R Package To Estimate Censored Autoregressive Time Series With Exogenous Covariates, Chao Wang, Kung-Sik Chan

The R Journal

We implement in the R package carx a novel and computationally efficient quasi-likelihood method for estimating a censored autoregressive model with exogenous covariates. The proposed quasi-likelihood method reduces to maximum likelihood estimation in absence of censoring. The carx package contains many useful functions for practical data analysis with censored stochastic regression, including functions for outlier detection, model diagnostics, and prediction with censored time series data. We illustrate the capabilities of the carx package with simulations and an elaborate real data analysis.

Furniture For Quantitative Scientists, Tyson S. Barrett, Emily Brignone

The R Journal

A basic understanding of the distributions of study variables and the relationships among them is essential to inform statistical modeling. This understanding is achieved through the computation of summary statistics and exploratory data analysis. Unfortunately, this step tends to be under-emphasized in the research process, in part because of the often tedious nature of thorough exploratory data analysis. The table1() function in the furniture package streamlines much of the exploratory data analysis process, making the computation and communication of summary statistics simple and beautiful while offering significant time-savings to the researcher

Ctmcd: An R Package For Estimating The Parameters Of A Continuous-Time Markov Chain From Discrete-Time Data, Marius Pfeuffer

The R Journal

This article introduces the R package ctmcd, which provides an implementation of methods for the estimation of the parameters of a continuous-time Markov chain given that data are only available on a discrete-time basis. This data consists of partial observations of the state of the chain, which are made without error at discrete times, an issue also known as the embedding problem for Markovchains. The functions provided comprise matrix logarithm based approximations as described in Israel et al. (2001), as well as Kreinin and Sidelnikova (2001), an expectation-maximization algorithm and a Gibbs sampling approach, both introduced by Bladt and …

Discrete Time Markov Chains With R, Giorgio Alfredo Spedicato

The R Journal

The markovchain package aims to provide S4 classes and methods to easily handle Discrete Time Markov Chains (DTMCs), filling the gap with what is currently available in the CRAN repository. In this work, I provide an exhaustive description of the main functions included in the package, as well as hands-on examples.

Fourierin: An R Package To Compute Fourier Integrals, Guillermo Basulto-Elias, Alicia Carriquiry, Kris De Brabanter, Daniel J. Nordman

The R Journal

We present the R package fourierin (Basulto-Elias, 2017) for evaluating functions defined as Fourier-type integrals over a collection of argument values. The integrals are finitely supported with integrands involving continuous functions of one or two variables. As an important application, such Fourier integrals arise in so-called “inversion formulas”, where one seeks to evaluate a probability density at a series of points from a given characteristic function (or vice versa) through Fourier transforms. This paper intends to fill a gap in current R software, where tools for repeated evaluation of functions as Fourier integrals are not directly available. We implement two …

Allele Imputation And Haplotype Determination From Databases Composed Of Nuclear Families, Nathan Medina-Rodríguez, Ángelo Santana

The R Journal

The alleHap package is designed for imputing genetic missing data and reconstruct non recombinant haplotypes from pedigree databases in a deterministic way. When genotypes of related individuals are available in a number of linked genetic markers, the program starts by identifying haplotypes compatible with the observed genotypes in those markers without missing values. If haplotypes are identified in parents or offspring, missing alleles can be imputed in subjects containing missing values. Several scenarios are analyzed: family completely genotyped, children partially genotyped and parents completely genotyped, children fully genotyped and parents containing entirely or partially missing genotypes, and founders and their …

Anchoreddistr: A Package For The Bayesian Inversion Of Geostatistical Parameters With Multi-Type And Multi-Scale Data, Heather Savoy, Falk Heße, Yoram Rubin

The R Journal

The Method of Anchored Distributions (MAD) is a method for Bayesian inversion designed for inferring both local (e.g. point values) and global properties (e.g. mean and variogram parameters) of spatially heterogenous fields using multi-type and multi-scale data. Software implementations of MAD exist in C++ and C# to import data, execute an ensemble of forward model simulations, and perform basic post-processing of calculating likelihood and posterior distributions for a given application. This article describes the R package anchoredDistr that has been built to provide an R based environment for this method. In particular, anchoredDistr provides a range of post-processing capabilities for …

Editorial, Roger Bivand

The R Journal

In my editorial for the 2017–1 issue, I concentrated on tabulating the status of this journal with respect to its authors and reviewers (updated tables below). This time, I was prompted by an interesting blog posting by Jan Wijffels of BNOSAC, describing the use of the udpipe package to apply natural language processing (NLP) to the CRAN package database available from tools::CRAN_package_db() since the release of R 3.4. The interactive NLP searcher is a dashboard permitting exploration of annotated CRAN package title and description NLP data.

Visualization Of Regression Models Using Visreg, Patrick Breheny, Woodrow Burchett

The R Journal

Regression models allow one to isolate the relationship between the outcome and an explanatory variable while the other variables are held constant. Here, we introduce an R package, visreg, for the convenient visualization of this relationship via short, simple function calls. In addition to estimates of this relationship, the package also provides pointwise confidence bands and partial residuals to allow assessment of variability as well as outliers and other deviations from modeling assumptions. The package provides several options for visualizing models with interactions, including lattice plots, contour plots, and both static and interactive perspective plots. The implementation of the …

Rqgis: Integrating R With Qgis For Statistical Geocomputing, Jannes Muenchow, Patrick Schratz, Alexander Brenning

The R Journal

Integrating R with Geographic Information Systems (GIS) extends R’s statistical capabilities with numerous geoprocessing and data handling tools available in a GIS. QGIS is one of the most popular open-source GIS, and it furthermore integrates other GIS programs such as the System for Automated Geoscientific Analyses (SAGA) GIS and the Geographic Resources Analysis Support System (GRASS) GIS within a single software environment. This and its QGIS Python API makes it a perfect candidate for console-based geoprocessing. By establishing an interface, the R package RQGIS makes it possible to use QGIS as a geoprocessing workhorse from within R. Compared to other …

A Tidy Data Model For Natural Language Processing Using Cleannlp, Taylor Arnold

The R Journal

Recent advances in natural language processing have produced libraries that extract low level features from a collection of raw texts. These features, known as annotations, are usually stored internally in hierarchical, tree-based data structures. This paper proposes a data model to represent annotations as a collection of normalized relational data tables optimized for exploratory data analysis and predictive modeling. The R package cleanNLP, which calls one of two state of the art NLP libraries (CoreNLP or spaCy), is presented as an implementation of this data model. It takes raw text as an input and returns a list of normalized …

R Foundation News, Torsten Hothorn

The R Journal

Donations and members

Donations

Supporting benefactors

Supporting members

Splitting It Up: The Spduration Split-Population Duration Regression Package For Time-Varying Covariates, Andreas Beger, Daniel W. Hill Jr, Nils W. Metternich, Shahryar Minhas, Michael D. Ward

The R Journal

We present an implementation of split-population duration regression in the spduration (Beger et al., 2017) package for R that allows for time-varying covariates. The statistical model accounts for units that are immune to a certain outcome and are not part of the duration process the researcher is primarily interested in. We provide insights for when immune units exist, that can significantly increase the predictive performance compared to standard duration models. The package includes estimation and several post-estimation methods for split-population Weibull and log-logistic models. Weprovide an empirical application to data on military coups.

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.4.3

Afmtoolkit: An R Package For Automated Afm Force-Distance Curves Analysis, Rafael Benítez, Vicente J. Bolós, José-Luis Toca-Herrera

The R Journal

Atomic force microscopy (AFM) is widely used to measure molecular and colloidal inter actions as well as mechanical properties of biomaterials. In this paper the afmToolkit R package is introduced. This package allows the user to automatically batch process AFM force-distance and force-time curves. afmToolkit capabilities range from importing ASCII files and preprocessing the curves (contact point detection, baseline correction...) for finding relevant physical information, such as Young’s modulus, adhesion energies and exponential decay for force relaxation and creep experiments. This package also contains plotting, summary and feature extraction functions. The package also comes with several data sets so the …

Learest: Length And Area Estimation From Data Measured With Additive Error, Mirta Benšić, Petar Taler, Safet Hamedović, Emmanuel Karlo Nyarko, Kristian Sabo

The R Journal

This paper describes an R package LeArEst that can be used for estimating object dimensions from a noisy image. The package is based on a simple parametric model for data that are drawn from uniform distribution contaminated by an additive error. Our package is able to estimate the length of the object of interest on a given straight line that intersects it, as well as to estimate the object area when it is elliptically shaped. The input data may be a numerical vector or an image in JPEG format. In this paper, background statistical models and methods for the package …

Manlymix: An R Package For Manly Mixture Modeling, Xuwen Zhu, Volodymyr Melnykov

The R Journal

Model-based clustering is a popular technique for grouping objects based on a finite mixture model. It has countless applications in different fields of study. The R package ManlyMix implements the Manly mixture model that allows modeling skewness within data groups and performs cluster analysis. ManlyMix is a powerful diagnostics tool that is capable of conducting investigation concerning the normality of variables upon fitting of a Manly forward or backward model. Theoretical foundations as well as description of functions are provided. All features of the package are illustrated with examples in great detail. The analysis of real-life datasets demonstrates the flexibility …

Rpsftm: An R Package For Rank Preserving Structural Failure Time Models, Annabel Allison, Ian R. White, Simon Bond

The R Journal

Treatment switching in a randomised controlled trial occurs when participants change from their randomised treatment to the other trial treatment during the study. Failure to account for treatment switching in the analysis (i.e. by performing a standard intention-to-treat analysis) can lead to biased estimates of treatment efficacy. The rank preserving structural failure time model (RPSFTM) is a method used to adjust for treatment switching in trials with survival outcomes. The RPSFTM is due to Robins and Tsiatis (1991) and has been developed by White et al. (1997, 1999).

The method is randomisation based and uses only the randomised treatment group, …

Simulating Probabilistic Long-Term Effects In Models With Temporal Dependence, Christopher Gandrud, Laron K. Williams

The R Journal

The R package pltesim calculates and depicts probabilistic long-term effects in binary models with temporal dependence variables. The package performs two tasks. First, it calculates the change in the probability of the event occurring given a change in a theoretical variable. Second, it calculates the rolling difference in the future probability of the event for two scenarios: one where the event occurred at a given time and one where the event does not occur. The package is consistent with the recent movement to depict meaningful and easy-to-interpret quantities of interest with the requisite measures of uncertainty. It is the first …

Conference Report: R In Insurance 2017, Nicolas Baradel, Christophe Dutang, Caroline Hillairet

The R Journal

The fifth R in Insurance conference took place at Ecole Nationale de la Statistique et de l’Administration Economique (ENSAE, one of the leading French graduate schools in the fields of statistics, economics, finance and actuarial science) Paris on 8 June 2017. This one-day conference focused once more on the wide range of applications of R in insurance, actuarial science and beyond. The conference programme covered topics including reserving, pricing, loss modelling, the use of R in a production environment and also new statistical methods such as big data analysis.

Bayesian Regression Models For Interval-Censored Data In R, Clifford Anderson-Bergman

The R Journal

The package icenReg provides classic survival regression models for interval-censored data. We present an update to the package that extends the parametric models into the Bayesian framework. Core additions include functionality to define the regression model with the standard regression syntax while providing a custom prior function. Several other utility functions are presented that allow for simplified examination of the posterior distribution.

Simulating Noisy, Nonparametric, And Multivariate Discrete Patterns, Ruby Sharma, Sajal Kumar, Hua Zhong, Mingzhou Song

The R Journal

Requiring no analytical forms, nonparametric discrete patterns are flexible in representing complex relationships among random variables. This makes them increasingly useful for data-driven applications. However, there appears to be no software tools for simulating nonparametric discrete patterns, which prevents objective evaluation of statistical methods that discover discrete relationships from data. We present a simulator to generate nonparametric discrete functions as contingency tables. User can request strictly many-to-one functional patterns. The simulator can also produce contingency tables representing dependent non-functional and independent relationships. An option is provided to apply random noise to contingency tables. We demonstrate the utility of the simulator …

Conference Report: User!2017, Tobias Verbeke

The R Journal

After a very successful 2016 edition in Stanford (US), the useR conference invited the R communitytomeetfromJuly4toJuly7inBrussels(Belgium), heart of Europe. The response was extraordinary: 1175 people (of 54 nationalities) travelled the globe to join for a week of intense exchange and discussion. The conference was held in the Wild Gallery which was– for the occasion– the exclusive territory of R aficionados with many co-hosted events including DSC 2017, RIOT 2017 and an R Foundation meeting.

An important theme throughout the conference was to be welcoming and inclusive. In this respect 25 diversity scholarships were awarded and newbies were welcomed at a …

Rentrez: An R Package For The Ncbi Eutils Api, David J. Winter

The R Journal

The USA National Center for Biotechnology Information (NCBI) is one of the world’s most important sources of biological information. NCBI databases like PubMed and GenBank contain mil lions of records describing bibliographic, genetic, genomic, and medical data. Here I present rentrez, a package which provides an R interface to 50 NCBI databases. The package is well-documented, contains an extensive suite of unit tests and has an active user base. The programmatic interface to the NCBI provided by rentrez allows researchers to query databases and download or import particular records into R sessions for subsequent analysis. The complete nature of …

Crtgeedr: An R Package For Doubly Robust Generalized Estimating Equations Estimations In Cluster Randomized Trials With Missing Data, Melanie Prague, Rui Wang, Victor De Gruttola

The R Journal

Semi-parametric approaches based on generalized estimating equations (GEE) are widely used to analyze correlated outcomes in longitudinal settings. In this paper, we present a package CRTgeeDR developed for cluster randomized trials with missing data (CRTs). For use of inverse probability weighting to adjust for missing data in cluster randomized trials, we show that other software lead to biased estimation for non-independence working correlation structure. CRTgeeDR solves this problem. We also extend the ability of existing packages to allow augmented Doubly Robust GEEestimation (DR). Simulation studies demonstrate the consistency of estimators implemented in CRTgeeDR compared to packages such as geepack and …