Open Access. Powered by Scholars. Published by Universities.®

University of Nebraska - Lincoln

Discipline
Keyword
Publication Year
Publication

Articles 691 - 720 of 747

Full-Text Articles in Numerical Analysis and Scientific Computing

Content-Based Social Network Analysis Of Mailing Lists, Angela Bohn, Ingo Feinerer, Kurt Hornik, Patrick Mair Dec 2011

Content-Based Social Network Analysis Of Mailing Lists, Angela Bohn, Ingo Feinerer, Kurt Hornik, Patrick Mair

The R Journal

Social Network Analysis (SNA) provides tools to examine relationships between people. Text Mining (TM) allows capturing the text they produce in Web 2.0 applications, for example, however it neglects their social structure. This paper applies an approach to combine the two methods named “content-based SNA”. Using the R mailing lists, R-help and R-devel, we show how this combination can be used to describe people’s interests and to find out if authors who have similar interests actually communicate. We find that the expected positive relationship between sharing interests and communicating gets stronger as the centrality scores of authors in the communication …


Watch Your Spelling!, Kurt Hornik, Duncan Murdoch Dec 2011

Watch Your Spelling!, Kurt Hornik, Duncan Murdoch

The R Journal

We discuss the facilities in base R for spell checking via Aspell, Hunspell or Ispell, which are useful in particular for conveniently checking the spelling of natural language texts in package Rd files and vignettes. Spell checking performance is illustrated using the Rd files in package stats. This example clearly indicates the need for a domain-specific statistical dictionary. We analyze the results of spell checking all Rd files in all CRAN packages and show how these can be employed for building such a dictionary.


Nonparametric Goodness-Of-Fit Tests For Discrete Null Distributions, Taylor B. Arnold, John W. Emerson Dec 2011

Nonparametric Goodness-Of-Fit Tests For Discrete Null Distributions, Taylor B. Arnold, John W. Emerson

The R Journal

Methodology extending nonparametric goodness-of-fit tests to discrete null distributions has existed for several decades. However, modern statistical software has generally failed to provide this methodology to users. We offer a revision of R’s ks.test() function and a new cvm.test() function that fill this need in the R language for two of the most popular nonparametric goodness-of-fit tests. This paper describes these contributions and provides examples of their usage. Particular attention is given to various numerical issues that arise in their implementation.


Portable C++ For R Packages, Martyn Plummer Dec 2011

Portable C++ For R Packages, Martyn Plummer

The R Journal

Package checking errors are more common on Solaris than Linux. In many cases, these errors are due to non-portable C++ code. This article reviews some commonly recurring problems in C++ code found in R packages and suggests solutions.


Glm2: Fitting Generalized Linear Models With Convergence Problems, Ian C. Marschner Dec 2011

Glm2: Fitting Generalized Linear Models With Convergence Problems, Ian C. Marschner

The R Journal

The R function glm uses step-halving to deal with certain types of convergence problems when using iteratively reweighted least squares to fit a generalized linear model. This works well in some circumstances but non-convergence remains a possibility, particularly with a non standard link function. In some cases this is be cause step-halving is never invoked, despite a lack of convergence. In other cases step-halving is invoked but is unable to induce convergence. One remedy is to impose a stricter form of step halving than is currently available in glm, so that the deviance is forced to decrease in every iteration. …


Creating And Deploying An Application With (R)Excel And R, Thomas Baier, Erich Neuwirth, Michele De Meo Dec 2011

Creating And Deploying An Application With (R)Excel And R, Thomas Baier, Erich Neuwirth, Michele De Meo

The R Journal

We present some ways of using R in Excel and build an example application using the package rpart. Starting with simple interactive use of rpart in Excel, we eventually package the code into an Excel-based application, hiding all details (including R itself) from the end user. In the end, our application implements a service oriented architecture (SOA) with a clean separation of presentation and computation layer


Grapher: A Multiplatform Gui For Drawing Customizable Graphs In R, Maxime Hervé Dec 2011

Grapher: A Multiplatform Gui For Drawing Customizable Graphs In R, Maxime Hervé

The R Journal

This article presents GrapheR, a Graphical User Interface allowing the user to draw customizable and high-quality graphs without knowing any R commands. Six kinds of graph are available: histograms, box-and-whisker plots, bar plots, pie charts, curves and scatter plots. The complete process is described with the examples of a bar plot and a scatter plot illustrating the legendary puzzle of African and European swallows’ migrations.


The R Journal (June 2011) 3(1): Complete Issue, The R Foundation Jun 2011

The R Journal (June 2011) 3(1): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

testthat: Get Started with Testing, Hadley Wickham

Content-Based Social Network Analysis of Mailing Lists, Angela Bohn, Ingo Feinerer, Kurt Hornik, and Patrick Mair

Rmetrics: timeDate Package, Yohan Chalabi, Martin Mächler, and Diethelm Würtz

The digitize Package: Extracting Numerical Data from Scatterplots, Timothée Poisot

Differential Evolution with DEoptim, David Ardia, Kris Boudt, Peter Carl, Katharine M. Mullen, and Brian G. Peterson

rworldmap: A New R Package for Mapping Global Data, Andy South

Cryptographic Boolean Functions with R, Frédéric Lafitte, Dirk Van Heule and Julien Van hamme

Raster Images in R Graphics, Paul Murrell

Probabilistic Weather Forecasting in R, …


Raster Images In R Graphics, Paul Murrell Jun 2011

Raster Images In R Graphics, Paul Murrell

The R Journal

The R graphics engine has new support for rendering raster images via the functions rasterImage() and grid.raster(). This leads to better scaling of raster images, faster rendering to screen, and smaller graphics files. Several examples of possible applications of these new features are described.


Cryptographic Boolean Functions With R, Frédéric Lafitte, Dirk Van Heule, Julien Van Hamme Jun 2011

Cryptographic Boolean Functions With R, Frédéric Lafitte, Dirk Van Heule, Julien Van Hamme

The R Journal

A new package called boolfun is avail able for R users. The package provides tools to handle Boolean functions, in particular for cryptographic purposes. This document guides the user through some (code) examples and gives a feel of what can be done with the package.


Rmetrics: Timedate Package, Yohan Chalabi, Martin Mächler, Diethelm Würtz Jun 2011

Rmetrics: Timedate Package, Yohan Chalabi, Martin Mächler, Diethelm Würtz

The R Journal

The management of time and holidays can prove crucial in applications that rely on historical data. Atypical example is the aggregation of a data set recorded in different time zones and under different daylight saving time rules. Be sides the time zone conversion function, which is well supported by default classes in R,one might need functions to handle special days or holidays. In this respect, the package timeDate enhances default date-time classes in R and brings new functionalities to time zone management and the creation of holiday calendars


The Digitize Package: Extracting Numerical Data From Scatterplots, Timothée Poisot Jun 2011

The Digitize Package: Extracting Numerical Data From Scatterplots, Timothée Poisot

The R Journal

I present the small R package digitize, designed to extract data from scatter plots with a simple method and suited to small datasets. I present an application of this method to the ex traction of data from a graph whose source is not available.


Analyzing An Electronic Limit Order Book, David Kane, Andrew Liu, Khanh Nguyen Jun 2011

Analyzing An Electronic Limit Order Book, David Kane, Andrew Liu, Khanh Nguyen

The R Journal

The orderbook package provides facilities for exploring and visualizing the data associated with an order book: the electronic collection of the outstanding limit orders for a financial instrument. This article provides an overview of the orderbook package and examples of its use.


Testthat: Get Started With Testing, Hadley Wickham Jun 2011

Testthat: Get Started With Testing, Hadley Wickham

The R Journal

Software testing is important, but many of us don’t do it because it is frustrating and boring. testthat is a new testing framework for R that is easy learn and use, and integrates with your existing workflow. This paper shows how, with illustrations from existing packages.


Rworldmap: A New R Package For Mapping Global Data, Andy South Jun 2011

Rworldmap: A New R Package For Mapping Global Data, Andy South

The R Journal

rworldmap is a relatively new package available on CRAN for the mapping and visualisation of global data. The vision is to make the display of global data easier, to facilitate understanding and communication. The initial focus is on data referenced by country or grid due to the frequency of use of such data in global assessments. Tools to link data referenced by country (either name or code) to a map, and then to display the map are provided as are functions to map global gridded data. Country and gridded functions accept the same arguments to specify the nature of categories …


Differential Evolution With Deoptim, David Ardia, Kris Boudt, Peter Carl, Katharine M. Mullen, Brian G. Peterson Jun 2011

Differential Evolution With Deoptim, David Ardia, Kris Boudt, Peter Carl, Katharine M. Mullen, Brian G. Peterson

The R Journal

The R package DEoptim implements the Differential Evolution algorithm. This algorithm is an evolutionary technique similar to classic genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex portfolio optimization problem.


Probabilistic Weather Forecasting In R, Chris Fraley, Adrian Raftery, Tilmann Gneiting, Mclean Sloughter, Veronica Berrocol Jun 2011

Probabilistic Weather Forecasting In R, Chris Fraley, Adrian Raftery, Tilmann Gneiting, Mclean Sloughter, Veronica Berrocol

The R Journal

This article describes two R packages for probabilistic weather forecasting, ensembleBMA, which offers ensemble post-processing via Bayesian model averaging (BMA), and Prob ForecastGOP, which implements the geostatistical output perturbation (GOP) method. BMA forecasting models use mixture distributions, in which each component corresponds to an ensemble member, and the form of the component distribution depends on the weather parameter (temperature, quantitative precipitation or wind speed). The model parameters are estimated from training data. The GOP technique uses geostatistical methods to produce probabilistic fore casts of entire weather fields for temperature or pressure, based on a single numerical forecast on …


The R Journal (December 2010) 2(2): Complete Issue, The R Foundation Dec 2010

The R Journal (December 2010) 2(2): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

Solving Differential Equations in R, Karline Soetaert, Thomas Petzoldt and R. Woodrow Setzer

Source References, Duncan Murdoch

hglm: A Package for Fitting Hierarchical Generalized Linear Models, Lars Rönnegård, Xia Shen and Moudud Alam

dclone: Data Cloning in R, Péter Sólymos

stringr: Modern, Consistent String Processing, Hadley Wickham

Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations, David Ardia and Lennart F. Hoogerheide

cudaBayesreg: Bayesian Computation in CUDA, Adelino Ferreira da Silva

binGroup: A Package for Group Testing, Christopher R. Bilder, Boan Zhang, Frank Schaarschmidt, and Joshua M. Tebbs

The RecordLinkage Package: Detecting Errors in Data, Murat Sariyar …


The Recordlinkage Package: Detecting Errors In Data, Murat Sariyar, Andreas Borg Dec 2010

The Recordlinkage Package: Detecting Errors In Data, Murat Sariyar, Andreas Borg

The R Journal

Record linkage deals with detecting homonyms and mainly synonyms in data. The package RecordLinkage provides means to per form and evaluate different record linkage methods. A stochastic framework is implemented which calculates weights through an EM algorithm. The determination of the necessary thresholds in this model can be achieved by tools of extreme value theory. Furthermore, machine learning methods are utilized, including decision trees (rpart), bootstrap aggregating (bagging), ada boost (ada), neural nets (nnet) and support vector machines (svm). The generation of record pairs and comparison patterns from single data …


Bingroup: A Package For Group Testing, Christopher R. Bilder, Boan Zhang, Frank Schaarschmidt, Joshua M. Tebbs Dec 2010

Bingroup: A Package For Group Testing, Christopher R. Bilder, Boan Zhang, Frank Schaarschmidt, Joshua M. Tebbs

The R Journal

When the prevalence of a disease or of some other binary characteristic is small, group testing (also known as pooled testing) is frequently used to estimate the prevalence and/or to identify individuals as positive or negative. We have developed the binGroup package as the first package designed to address the estimation problem in group testing. We present functions to estimate an overall prevalence for a homogeneous population. Also, for this set ting, we have functions to aid in the very important choice of the group size. When individuals come from a heterogeneous population, our group testing regression functions can be …


Stringr: Modern, Consistent String Processing, Hadley Wickham Dec 2010

Stringr: Modern, Consistent String Processing, Hadley Wickham

The R Journal

String processing is not glamorous, but it is frequently used in data cleaning and preparation. The existing string functions in R are powerful, but not friendly. To remedy this, the stringr package provides string functions that are simpler and more consistent, and also fixes some functionality that R is missing compared to other programming languages.


Source References, Duncan Murdoch Dec 2010

Source References, Duncan Murdoch

The R Journal

Since version 2.10.0, R includes expanded support for source references in R code and ‘.Rd’ files. This paper describes the origin and purposes of source references, and current and future support for them.


Mapping And Measuring Country Shapes, Nils B. Weidmann, Kristian Skrede Gleditsch Dec 2010

Mapping And Measuring Country Shapes, Nils B. Weidmann, Kristian Skrede Gleditsch

The R Journal

The article introduces the cshapes R package, which includes our CShapes dataset of contemporary and historical country boundaries, as well as computational tools for computing geographical measures from these maps. We provide an overview of the need for considering spatial dependence in comparative re search, how this requires appropriate historical maps, and detail how the cshapes associated R package cshapes can contribute to these ends. We illustrate the use of the package for drawing maps, computing spatial variables for countries, and generating weights matrices for spatial statistics.


Dclone: Data Cloning In R, Péter Sólymos Dec 2010

Dclone: Data Cloning In R, Péter Sólymos

The R Journal

The dclone R package contains low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov Chain Monte Carlo methods with support for JAGS, WinBUGS and OpenBUGS.


Solving Differential Equations In R, Karline Soetaert, Thomas Petzoldt, R. Woodrow Setzer Dec 2010

Solving Differential Equations In R, Karline Soetaert, Thomas Petzoldt, R. Woodrow Setzer

The R Journal

Although R is still predominantly applied for statistical analysis and graphical representation, it is rapidly becoming more suitable for mathematical computing. One of the fields where considerable progress has been made recently is the solution of differential equations. Here we give a brief overview of differential equations that can now be solved by R.


Spikeslab: Prediction And Variable Selection Using Spike And Slab Regression, Hemant Ishwaran, Udaya B. Kogalur, J. Sunil Rao Dec 2010

Spikeslab: Prediction And Variable Selection Using Spike And Slab Regression, Hemant Ishwaran, Udaya B. Kogalur, J. Sunil Rao

The R Journal

Weighted generalized ridge regression offers unique advantages in correlated high dimensional problems. Such estimators can be efficiently computed using Bayesian spike and slab models and are effective for prediction. For sparse variable selection, a generalization of the elastic net can be used in tandem with these Bayesian estimates. In this article, we de scribe the R-software package spikeslab for implementing this new spike and slab prediction and variable selection methodology.


Hglm: A Package For Fitting Hierarchical Generalized Linear Models, Lars Rönnegård, Xia Shen, Moudud Alam Dec 2010

Hglm: A Package For Fitting Hierarchical Generalized Linear Models, Lars Rönnegård, Xia Shen, Moudud Alam

The R Journal

We present the hglm package for fit ting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.


Bayesian Estimation Of The Garch(1,1) Model With Student-T Innovations, David Ardia, Lennart F. Hoogerheide Dec 2010

Bayesian Estimation Of The Garch(1,1) Model With Student-T Innovations, David Ardia, Lennart F. Hoogerheide

The R Journal

This note presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning an MCMC sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns


Online Reproducible Research: An Application To Multivariate Analysis Of Bacterial Dna Fingerprint Data, Jean Thioulouse, Claire Valiente-Moro, Lionel Zenner Dec 2010

Online Reproducible Research: An Application To Multivariate Analysis Of Bacterial Dna Fingerprint Data, Jean Thioulouse, Claire Valiente-Moro, Lionel Zenner

The R Journal

This paper presents an example of online reproducible multivariate data analysis. This example is based on a web page providing an online computing facility on a server. HTML forms contain editable R code snippets that can be executed in any web browser thanks to the Rweb software. The example is based on the multivariate analysis of DNA fingerprints of the internal bacterial flora of the poultry red mite Dermanyssus gallinae. Several multivariate data analysis methods from the ade4 package are used to compare the fingerprints of mite pools coming from various poultry farms. All the computations and graphical displays …


Cudabayesreg: Bayesian Computation In Cuda, Adelino Ferreira Da Silva Dec 2010

Cudabayesreg: Bayesian Computation In Cuda, Adelino Ferreira Da Silva

The R Journal

Graphical processing units are rapidly gaining maturity as powerful general parallel computing devices. The package cudaBayesreg uses GPU–oriented procedures to improve the performance of Bayesian computations. The paper motivates the need for devising high performance computing strategies in the con text of fMRI data analysis. Some features of the package for Bayesian analysis of brain fMRI data are illustrated. Comparative computing performance figures between sequential and parallel implementations are presented as well.