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Full-Text Articles in Numerical Analysis and Scientific Computing

Allele Imputation And Haplotype Determination From Databases Composed Of Nuclear Families, Nathan Medina-Rodríguez, Ángelo Santana Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 Dec 2017

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 …


Bayesbd: An R Package For Bayesian Inference On Image Boundaries, Nicholas Syring, Meng Li Dec 2017

Bayesbd: An R Package For Bayesian Inference On Image Boundaries, Nicholas Syring, Meng Li

The R Journal

Wepresent the BayesBD package providing Bayesian inference for boundaries of noisy images. The BayesBD package implements flexible Gaussian process priors indexed by the circle to recover the boundary in a binary or Gaussian noised image. The boundary recovered by BayesBD has the practical advantages of guaranteed geometric restrictions and convenient joint inferences under certain assumptions, in addition to its desirable theoretical property of achieving (nearly) minimax optimal rate in a way that is adaptive to the unknown smoothness. The core sampling tasks for our model have linear complexity, and are implemented in C++ for computational efficiency using packages Rcpp and …


Adegraphics: An S4 Lattice-Based Package For The Representation Of Multivariate Data, Aurélie Siberchicot, Alice Julien-Laferrière, Anne-Béatrice Dufour, Jean Thioulouse, Stéphane Dray Dec 2017

Adegraphics: An S4 Lattice-Based Package For The Representation Of Multivariate Data, Aurélie Siberchicot, Alice Julien-Laferrière, Anne-Béatrice Dufour, Jean Thioulouse, Stéphane Dray

The R Journal

The ade4 package provides tools for multivariate analyses. Whereas new statistical methods have been added regularly in the package since its first release in 2002, the graphical functions, that are used to display the main outputs of an analysis, have not benefited from such enhancements. In this context, the adegraphics package, available on CRAN since 2015, is a complete reimplementation of the ade4 graphical functionalities but with large improvements. The package uses the S4 object system (each graph is an object) and is based on the graphical framework provided by lattice and grid. We give a brief description of the …


Arulesviz: Interactive Visualization Of Association Rules With R, Michael Hahsler Dec 2017

Arulesviz: Interactive Visualization Of Association Rules With R, Michael Hahsler

The R Journal

Association rule mining is a popular data mining method to discover interesting relation ships between variables in large databases. An extensive toolbox is available in the R-extension package arules. However, mining association rules often results in a vast number of found rules, leaving the analyst with the task to go through a large set of rules to identify interesting ones. Sifting manually through extensive sets of rules is time-consuming and strenuous. Visualization and especially interactive visualization has a long history of making large amounts of data better accessible. The R-extension package arulesViz provides most popular visualization techniques for association …


Queueing: A Package For Analysis Of Queueing Networks And Models In R, Pedro Cañadilla Jiménez, Yolanda Román Montoya Dec 2017

Queueing: A Package For Analysis Of Queueing Networks And Models In R, Pedro Cañadilla Jiménez, Yolanda Román Montoya

The R Journal

queueing is a package that solves and provides the main performance measures for both basic Markovian queueing models and single and multiclass product-form queueing networks. It can be used both in education and for professional purposes. It provides an intuitive, straightforward wayto build queueing models using S3 methods. The package solves Markovian models of the form M/M/c/K/M/FCFS, open and closed single class Jackson networks, open and closed multiclass networks and mixed networks. Markovian models are used when both the customer inter-arrival time and the server processing time are exponentially distributed. Queueing network solvers are useful for modelling situations in which …


Glmmtmb Balances Speed And Flexibility Among Packages For Zero-Inflated Generalized Linear Mixed Modeling, Mollie E. Brooks, Kasper Kristensen, Koen J. Van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Mächler, Benjamin M. Bolker Dec 2017

Glmmtmb Balances Speed And Flexibility Among Packages For Zero-Inflated Generalized Linear Mixed Modeling, Mollie E. Brooks, Kasper Kristensen, Koen J. Van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Mächler, Benjamin M. Bolker

The R Journal

Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inflated mixed models. The glmmTMB package fits many types of GLMMs and extensions, including models with continuously distributed responses, but here we focus on count responses. glmmTMB is faster than glmmADMB, MCMCglmm, and brms, and more flexible than INLA and mgcv for zero-inflated …


Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad Dec 2017

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

School of Computing: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …


Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam Jul 2017

Querying And Visualization Of Moving Objects Using Constraint Databases, Semere M. Woldemariam

School of Computing: Dissertations, Theses, and Student Research

Good querying and visualization of moving objects and their trajectories is still an open problem. This thesis investigates three types of moving objects. First, projectiles, whose parabolic motion is difficult to represent. Second, moving objects that slide down a slope. The representation of these objects is challenging because of their accelerating motion. Third, the motion of migrating animals. The motion of migrating animals is challenging because it also involves some spatio-temporal interpolation. The thesis shows a solution to these problems using ideas from physics and an implementation in the MLPQ constraint databases system. The MLPQ implementation enables several complex spatio-temporal …


The R Journal (June 2017) 9(1): Complete Issue, The R Foundation Jun 2017

The R Journal (June 2017) 9(1): Complete Issue, The R Foundation

The R Journal

Editorial, Roger Bivand

Contributed Research Articles

iotools: High-Performance I/O Tools for R, Taylor Arnold, Michael J. Kane, and Simon Urbanek

IsoGeneGUI: Multiple Approaches for Dose-Response Analysis of Microarray Data Using R, Martin Otava, Rudradev Sengupta, Ziv Shkedy, Dan Lin, Setia Pramana, Tobias Verbeke, Philippe Haldermans, Ludwig A. Hothorn, Daniel Gerhard, Rebecca M. Kuiper, Florian Klinglmueller, and Adetayo Kasim

Network Visualization with ggplot2, Sam Tyner, François Briatte, and Heike Hofmann

OrthoPanels: An R Package for Estimating a Dynamic Panel Model with Fixed Effects Using the Orthogonal Reparameterization Approach, Mark Pickup, Paul Gustafson, Davor Cubranic, and Geoffrey Evans

The mosaic Package: Helping …


The Noisefiltersr Package: Label Noise Preprocessing In R, Pablo Morales, Julián Luengo, Luís P.F. Garcia, Ana C. Lorena, André C.P.L.F. De Carvalho Jun 2017

The Noisefiltersr Package: Label Noise Preprocessing In R, Pablo Morales, Julián Luengo, Luís P.F. Garcia, Ana C. Lorena, André C.P.L.F. De Carvalho

The R Journal

In Data Mining, the value of extracted knowledge is directly related to the quality of the used data. This makes data preprocessing one of the most important steps in the knowledge discovery process. A common problem affecting data quality is the presence of noise. A training set with label noise can reduce the predictive performance of classification learning techniques and increase the overfitting of classification models. In this work we present the NoiseFiltersR package. It contains the first extensive R implementation of classical and state-of-the-art label noise filters, which are the most common techniques for preprocessing label noise. The algorithms …


Hosting Data Packages Via Drat: A Case Study With Hurricane Exposure Data, G Brooke Anderson, Dirk Eddelbuettel Jun 2017

Hosting Data Packages Via Drat: A Case Study With Hurricane Exposure Data, G Brooke Anderson, Dirk Eddelbuettel

The R Journal

Data-only packages offer a way to provide extended functionality for other R users. However, such packages can be large enough to exceed the package size limit (5 megabytes) for the Comprehensive R Archive Network (CRAN). As an alternative, large data packages can be posted to additional repostiories beyond CRAN itself in a way that allows smaller code packages on CRAN to access and use the data. The drat package facilitates creation and use of such alternative repositories and makes it particularly simple to host them via GitHub. CRAN packages can draw on packages posted to drat repositories through the use …