Numerical Analysis and Scientific Computing Commons^™

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 …

Clustering.Sc.Dp: Optimal Clustering With Sequential Constraint By Using Dynamic Programming, Tibor Szkaliczki

The R Journal

The general clustering algorithms do not guarantee optimality because of the hardness of the problem. Polynomial-time methods can find the clustering corresponding to the exact optimum only in special cases. For example, the dynamic programming algorithm can solve the one-dimensional clustering problem, i.e., when the items to be clustered can be characterised by only one scalar number. Optimal one-dimensional clustering is provided by package Ckmeans.1d.dp in R. The paper shows a possible generalisation of the method implemented in this package to multidimensional data: the dynamic programming method can be applied to find the optimum clustering of vectors when only subsequent …

Fwdselect: An R Package For Variable Selection In Regression Models, Marta Sestelo, Nora M. Villanueva, Luis Meira-Machado, Javier Roca-Pardiñas

The R Journal

In multiple regression models, when there are a large number (p) of explanatory variables which may o rmay not be relevant for predicting the response, it is useful to be able to reduce the model. To this end, it is necessary to determine the best subset of q (q p) predictors which will establish the model with the best prediction capacity. FWDselect package introduces a new forward stepwise based selection procedure to select the best model in different regression frameworks (parametric or nonparametric). The developed methodology, which can be equally applied to linear models, generalized linear models or generalized additive …

News From The Bioconductor Project, Bioconductor Team

The R Journal

The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. The 1211 software packages available in Bioconductor can be viewed at http://bioconductor.org/packages/. Navigate packages using ‘biocViews’ terms and title search. Each package has an html page with a description, links to vignettes, reference manuals, and usage statistics. Start using Bioconductor version 3.3 by installing R 3.3.1 and evaluating the commands

R Packages To Aid In Handling Web Access Logs, Oliver Keyes, Bob Rudis, Jay Jacobs

The R Journal

Web access logs contain information on HTTP(S) requests and form a key part of both industry and academic explorations of human behaviour on the internet. But the preparation (reading, parsing and manipulation) of that data is just unique enough to make generalized tools unfit for the task, both in programming time and processing time which are compounded when dealing with large data sets common with web access logs. In this paper we explain and demonstrate a series of packages designed to efficiently read in, parse and munge access log data, allowing researchers to handle URLs and IP addresses easily. These …

An Interactive Survey Application For Validating Social Network Analysis Techniques, Mitchell Joblin, Wolfgang Mauerer

The R Journal

Social network analysis is extremely well supported by the R community and is routinely used for studying the relationships between people engaged in collaborative activities. While there has been rapid development of new approaches and metrics in this field, the challenging question of validity (how well insights derived from social networks agree with reality) is often difficult to address. We propose the use of several R packages to generate interactive surveys that are specifically well suited for validating social network analyses. Using our web-based survey application, we were able to validate the results of applying community-detection algorithms to infer the …

Conference Report: User! 2016, Joe Rickert

The R Journal

The 12th international R user conference, useR! 2016, took place at Stanford University, Stanford CA fromJune27throughJune30th. Hosted by the Stanford University Department of Statistics and the Stanford Libraries, the conference took place at the Frances Arrillaga Alumni Center, on the surrounding lawns and in several adjacent buildings. The floor to ceiling windows of the larger conference rooms, the garden locations for coffee and meals and the beautiful weather contributed to making the event a classic California experience.

Schemaonread: A Package For Schema-On-Read In R, Michael J. North

The R Journal

SchemaOnRead is a CRAN package that provides an extensible mechanism for importing a wide range of file types into R as well as support for the emerging schema-on-read paradigm in R. The schema-on-read tools within the package include a single function call that recursively reads folders with text, comma separated value, raster image, R data, HDF5, NetCDF, spreadsheet, Weka, Epi Info, Pajek network, R network, HTML, SPSS, Systat, and Stata files. It also recursively reads folders (e.g., schemaOnRead("folder")), returning a nested list of the contained elements. The provided tools can be used as-is or easily customized to implement tool chains …

Keyplayer: An R Package For Locating Key Players In Social Networks, Weihua An, Yu-Hsin Liu

The R Journal

Interest in social network analysis has exploded in the past few years, partly thanks to the advancements in statistical methods and computing for network analysis. A wide range of the methods for network analysis is already covered by existent R packages. However, no comprehensive packages are available to calculate group centrality scores and to identify key players (i.e., those players who constitute the most central group) in a network. These functionalities are important because, for example, many social and health interventions rely on key players to facilitate the intervention. Identifying key players is challenging because players who are individually the …

Rtableicc: An R Package For Random Generation Of 22k And Rc Contingency Tables, Haydar Demirhan

The R Journal

In this paper, we describe the R package rTableICC that provides an interface for random generation of 2 2 K and R Ccontingency tables constructed over either intraclass-correlated or uncorrelated individuals. Intraclass correlations arise in studies where sampling units include more than one individual and these individuals are correlated. The package implements random generation of contingency tables over individuals with or without intraclass correlations under various sampling plans. The package include two functions for the generation of K 2 2 tables over product-multinomial sampling schemes and that of 2 2 K tables under Poisson or multinomial sampling plans. It also …

Crowdsourced Data Preprocessing With R And Amazon Mechanical Turk, Thomas J. Leeper

The R Journal

This article introduces the use of the Amazon Mechanical Turk (MTurk) crowdsourcing platform as a resource for R users to leverage crowdsourced human intelligence for preprocessing “messy” data into a form easily analyzed within R. The article first describes MTurk and the MTurkR package, then outlines how to use MTurkR to gather and manage crowdsourced data with MTurk using some of the package’s core functionality. Potential applications of MTurkR include construction of manually coded training sets, human transcription and translation, manual data scraping from scanned documents, content analysis, image classification, and the completion of online survey questionnaires, among others. As …

Exploring Interaction Effects In Two-Factor Studies Using The Hiddenf Package In R., Christopher Franck, Jason A. Osborne

The R Journal

In crossed, two-factor studies with one observation per factor-level combination, interaction effects between factors can be hard to detect and can make the choice of a suitable statistical model difficult. This article describes hiddenf, an R package that enables users to quantify and characterize a certain form of interaction in two-factor layouts. When effects of one factor (a) fall into two groups depending on the level of another factor, and (b) are constant within these groups, the interaction pattern is deemed "hidden additivity" because within groups, the effects of the two factors are additive, while between groups the factors …

Gmdh: An R Package For Short Term Forecasting Via Gmdh-Type Neural Network Algorithms, Osman Dag, Ceylan Yozgatligil

The R Journal

Group Method of Data Handling (GMDH)-type neural network algorithms are the heuristic self organization method for the modelling of complex systems. GMDH algorithms are utilized for a variety of purposes, examples include identification of physical laws, the extrapolation of physical fields, pattern recognition, clustering, the approximation of multidimensional processes, forecasting without models, etc. In this study, the R package GMDH is presented to make short term forecasting through GMDH-type neural network algorithms. The GMDH package has options to use different transfer functions (sigmoid, radial basis, polynomial, and tangent functions) simultaneously or separately. Data on cancer death rate of Pennsylvania from …

The R Journal (August 2016) 8(1): Complete Issue, The R Foundation

The R Journal

Editorial, Michael Lawrence

Contributed Research Articles

metaplus: An R Package for the Analysis of Robust Meta-Analysis and Meta-Regression, Ken J. Beath

Gender Prediction Methods Based on First Names with genderizeR, Kamil Wais

Conditional Fractional Gaussian Fields with the Package FieldSim, Alexandre Brouste, Jacques Istas, and Sophie Lambert-Lacroix

rTableICC: An R Package for Random Generation of 22K and RC Contingency Tables, Haydar Demirhan

Maps, Coordinate Reference Systems and Visualising Geographic Data with mapmisc, Patrick E. Brown

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

Stylometry with R: A Package for …

Spica: Stereographic Projection For Interactive Crystallographic Analysis, Xingzhong Li

Nebraska Center for Materials and Nanoscience: Faculty Publications

In numerous research fields, especially the applications of electron and X-ray diffraction, stereographic projection represents a powerful tool for researchers. SPICA is a new computer program for stereographic projection in interactive crystallographic analysis, which inherits features from the previous JECP/SP and includes more functions for extensive crystallographic analysis. SPICA provides fully interactive options for users to plot stereograms of crystal directions and crystal planes, traces, and Kikuchi maps for an arbitrary crystal structure; it can be used to explore the orientation relationships between two crystalline phases with a composite stereogram; it is also used to predict the tilt angles of …

Estimability Tools For Package Developers, Russell V. Lenth

The R Journal

When a linear model is rank-deficient, then predictions based on that model become questionable because not all predictions are uniquely estimable. However, some of them are, and the estimability package provides tools that package developers can use to tell which is which. With the use of these tools, a model object’s predict method could return estimable predictions as-is while f lagging non-estimable ones in some way, so that the user can know which predictions to believe. The estimability package also provides, as a demonstration, an estimability-enhanced epredict method to use in place of predict for models fitted using the stats …

Alignment For Comprehensive Two-Dimensional Gas Chromatography (Gcxgc) With Global, Low-Order Polynomial Transformations, Davis Rempe, Stephen Reichenbach, Stephen Scott

UCARE: Research Products

As columns age and differ between systems, retention times for GC x GC may vary between runs. In order to properly analyze chromatograms, it is often desirable to align chromatographic features between chromatograms. This alignment can be characterized by a mapping of retention times from one chromatogram to the retention times of another chromatogram. Alignment methods can be classified as global or local, i.e., whether the geometric differences between chromatograms are characterized by a single function for the entire chromatogram or by a combination of many functions for different regions of the chromatogram. Previous work has shown that global, low-degree …

Image Harvest: An Open-Source Platform For High-Throughput Plant Image Processing And Analysis, Avi C. Knecht, Malachy T. Campbell, Adam Caprez, David R. Swanson, Harkamal Walia

Holland Computing Center: Faculty Publications

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources …

The R Journal (December 2015) 7(2): Complete Issue, The R Foundation

The R Journal

Editorial, Bettina Grün

Contributed Research Articles

Fitting Conditional and Simultaneous Autoregressive Spatial Models in hglm, Moudud Alam, Lars Rönnegård, and Xia Shen

VSURF: An R Package for Variable Selection Using Random Forests, Robin Genuer, Jean-Michel Poggi, and Christine Tuleau-Malot

zoib: An R Package for Bayesian Inference for Beta Regression and Zero/One Inflated Beta Regression, Fang Liu, and Yunchuan Kong

apc: An R Package for Age-Period-Cohort Analysis, Bent Nielsen

QuantifQuantile: An R Package for Performing Quantile Regression Through Optimal Quantization, Isabelle Charlier, Davy Paindaveine, and Jérôme Saracco

Numerical Evaluation of the Gauss Hypergeometric Function with the hypergeo Package, Robin K. S. …

An R Package For The Panel Approach Method For Program Evaluation: Pampe, Ainhoa Vega-Bayo

The R Journal

The pampe package for R implements the panel data approach method for program evaluation designed to estimate the causal effects of political interventions or treatments. This procedure exploits the dependence among cross-sectional units to construct a counterfactual of the treated unit(s), and it is an appropriate method for research events that occur at an aggregate level like countries or regions and that affect only one or a small number of units. The implementation of the pampe package is illustrated using data from Hong Kong and 24 other units, by examining the economic impact of the political and economic integration of …