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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

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

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

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

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

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

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

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

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

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

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

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

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.

Functional Reactive Musical Performers, Justin M. Phillips

Master's Theses

Computers have been assisting in recording, sound synthesis and other fields of music production for quite some time. The actual performance of music continues to be an area in which human players are chosen over computer performers. Musical performance is an area in which personalization is more important than consistency. Human players play with each other, reacting to phrases and ideas created by the players that they are playing with. Computer performers lack the ability to react to the changes in the performance that humans perceive naturally, giving the human players an advantage over the computer performers.

This thesis creates …

Automatic Execution Path Finding Tool, Fan Yang

Master's Projects

Today, there are many hackers trying to break software using reverse engineering tech- niques. To better protect software, we need to understand reverse engineering methods. This project presents a tool that automatically analyzes executable code in a manner simi- lar to the way an attack might analyze code.

Using reverse engineering techniques, executables can be disassembled to yield an as- sembly code representation of the program. Assembly code is much more human reada- ble than binary code. With assembly code, an attacker can attempt to modify the program to do something other than what was intended by the developer.

The …

Xpath-Based Template Language For Describing The Placement Of Metadata Within A Document, Vijay Kumar Musham

Computer Science Theses & Dissertations

In the recent years, there has been a tremendous growth in Internet and online resources that had previously been restricted to paper archives. OCR (Optical Character Recognition) tools can be used for digitalizing an existing corpus and making it available online. A number of federal agencies, universities, laboratories, and companies are placing their collections online and making them searchable via metadata fields such as author, title, and publishing organization. Manually creating metadata for a large collection is an extremely time-consuming task, and is difficult to automate, particularly for collections consisting of documents with diverse layout and structure. The Extract project …

Model Checking Hierarchical Probabilistic Systems, Jun Sun, Songzheng Song, Yang Liu

Research Collection School Of Computing and Information Systems

Probabilistic modeling is important for random distributed algorithms, bio-systems or decision processes. Probabilistic model checking is a systematic way of analyzing finite-state probabilistic models. Existing probabilistic model checkers have been designed for simple systems without hierarchy. In this paper, we extend the PAT toolkit to support probabilistic model checking of hierarchical complex systems. We propose to use PCSP#, a combination of Hoare’s CSP with data and probability, to model such systems. In addition to temporal logic, we allow complex safety properties to be specified by non-probabilistic PCSP# model. Validity of the properties (with probability) is established by refinement checking. Furthermore, …

Model Checking A Model Checker: A Code Contract Combined Approach, Jun Sun, Yang Liu, Bin Cheng

Research Collection School Of Computing and Information Systems

Model checkers, like any complex software, are subject to bugs. Unlike ordinary software, model checkers are often used to verify safety critical systems. Their correctness is thus vital. Verifying model checkers is extremely challenging because they are always complicated in logic and highly optimized. In this work, we propose a code contract combined approach for checking model checkers and apply it to a home-grown model checker PAT. In this approach, we firstly embed programming contracts (i.e., pre/post-conditions and invariants) into its source code, which can capture correctness of model checking algorithms, underlying data structures, consistency between different model checking parameters, …

Inductive Inference Of Languages From Samplings, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

We introduce, discuss, and study a model for inductive inference from samplings, formalizing an idea of learning different “projections” of languages. One set of our results addresses the problem of finding a uniform learner for all samplings of a language from a certain set when learners for particular samplings are available. Another set of results deals with extending learnability from a large natural set of samplings to larger sets. A number of open problems is formulated.

A Comparative Analysis Of Ascii And Xml Logging Systems, Eric C. Hanington

Theses and Dissertations

This research compares XML and ASCII based event logging systems in terms of their storage and processing efficiency. XML has been an emerging technology, even for security. Therefore, it is researched as a logging system with the mitigation of its verbosity. Each system consists of source content, the network transmission, database storage, and querying which are all studied as individual parts. The ASCII logging system consists of the text file as source, FTP as transport, and a relational database system for storage and querying. The XML system has the XML files and XML files in binary form using Efficient XML …

Enumeration Refactoring: A Tool For Automatically Converting Java Constants To Enumerated Types, Raffi Khatchadourian, Benjamin Muskalla

Publications and Research

Java 5 introduces several new features that significantly improve older Java technology. We consider the new enum construct, which provides language support for enumerated types. Before Java 5, programmers needed to employ various patterns to compensate for the absence of enumerated types in Java. Unfortunately, these compensation patterns lack several highly desirable properties of the enum construct, notably type-safety. We demonstrate an automated refactoring tool called Convert Constants to Enum for transforming legacy Java code to use the new enumeration construct. An interprocedural type inferencing algorithm that tracks the flow of enumerated values drives the approach, and the tool is …

Developing Model Checkers Using Pat, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

During the last two decades, model checking has emerged as an effective system analysis technique complementary to simulation and testing. Many model checking algorithms and state space reduction techniques have been proposed. Although it is desirable to have dedicated model checkers for every language (or application domain), implementing one with effective reduction techniques is rather challenging. In this work, we present a generic and extensible framework PAT, which facilitates users to build customized model checkers. PAT provides a library of state-of-art model checking algorithms as well as support for customizing language syntax, semantics, state space reduction techniques, graphic user interfaces, …

Visual Occam: High Level Visualization And Design Of Process Networks, Mikolaj M. Slomka

UNLV Theses, Dissertations, Professional Papers, and Capstones

With networks, multiprocessors, and multi-threaded systems becoming more common in our world it is increasingly evident that concurrent programming is not something to be ignored or marginalized even though many takes on concurrency (mainly by means of monitors or shared resources) have proven to be difficult to deal with on large scales. Thankfully, a good deal of work has already been done to combat this, through CSP, occam, and other such derivatives, to produce a scalable process oriented paradigm. Still, it is cumbersome to attempt to deal with the intricacies of such communicating networks down to every minutia; if, instead, …

The Executable Command In Support Of Scheduled Subroutine Calls, Andrew Scott Lewis

Electrical & Computer Engineering Theses & Dissertations

A potential solution to improving the utilization of increased thread level parallelism available in modern general purpose CPU's is the inclusion of a hardware scheduler. The hardware scheduler is designed to schedule subroutine calls based on a numerical condition in a high performance memory located on the CPU die, due to which the size of available memory is extremely limited. The main stumbling block in the development of a feasible hardware scheduler is the lack of a method of invoking a scheduled call using a single pointer. The use of a single pointer allows the limited size of the memory …

The R Journal (June 2010) 2(1): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

IsoGene: An R Package for Analyzing Dose-response Studies in Microarray Experiments, Setia Pramana, Dan Lin, Philippe Haldermans, Ziv Shkedy, Tobias Verbeke, Hinrich Göhlmann, An De Bondt, Willem Talloen, and Luc Bijnens

MCMC for Generalized Linear Mixed Models with glmmBUGS, Patrick Brown and Lutong Zhou

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

tmvtnorm: A Package for the Truncated Multivariate Normal Distribution, Stefan Wilhelm and B. G. Manjunath

neuralnet: Training of Neural Networks, Frauke Günther and Stefan Fritsch

glmperm: A Permutation of Regressor Residuals Test for Inference in Generalized Linear Models, Wiebke Werft and …

Isogene: An R Package For Analyzing Dose-Response Studies In Microarray Experiments, Setia Pramana, Dan Lin, Philippe Haldermans, Ziv Shkedy, Tobias Verbeke, Hinrich Göhlmann, An De Bondt, Williem Talloen, Luc Bijnens

The R Journal

IsoGene is an R package for the analysis of dose-response microarray experiments to identify gene or subsets of genes with a mono tone relationship between the gene expression and the doses. Several testing procedures (i.e., the likelihood ratio test, Williams, Marcus, the M, and Modified M), that take into account the order restriction of the means with respect to the increasing doses are implemented in the package. The inference is based on resampling methods, both permutations and the Significance Analysis of Microarrays (SAM).

Two-Sided Exact Tests And Matching Confidence Intervals For Discrete Data, Michael P. Fay

The R Journal

There is an inherent relationship between two-sided hypothesis tests and confidence intervals. A series of two-sided hypothesis tests may be inverted to obtain the matching 100(1-)% confidence interval defined as the smallest interval that contains all point null parameter values that would not be rejected at the α level. Unfortunately, for discrete data there are several different ways of defining two-sided exact tests and the most commonly used two sided exact tests are defined one way, while the most commonly used exact confidence intervals are inversions of tests defined another way. This can lead to inconsistencies where the exact test …

Neuralnet: Training Of Neural Networks, Franke Günther, Stefan Fritsch

The R Journal

Artificial neural networks are applied in many situations. neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables. Thus, neural networks are used as extensions of generalized linear models. neuralnet is a very flexible package. The back propagation algorithm and three versions of resilient back-propagation are implemented and it provides a custom-choice of activation and error function. An arbitrary number of covariates and response variables as well as of hidden layers can theoretically be included. The paper gives a brief introduction to multi-layer perceptrons and resilient back-propagation …

Mcmc For Generalized Linear Mixed Models With Glmmbugs, Patrick Brown, Lutong Zhou

The R Journal

The glmmBUGS package is a bridging tool between Generalized Linear Mixed Models (GLMMs) in R and the BUGS language. It provides a simple way of performing Bayesian inference using Markov Chain Monte Carlo (MCMC) methods, taking a model formula and data frame in R and writing a BUGS model file, data file, and initial values files. Functions are provided to reformat and summarize the BUGS results. A key aim of the package is to provide files and objects that can be modified prior to calling BUGS, giving users a platform for customizing and extending the models to accommodate a wide …

Glmperm: A Permutation Of Regressor Residuals Test For Inference In Generalized Linear Models, Wiebke Werft, Axel Benner

The R Journal

We introduce a new R package called glmperm for inference in generalized linear models especially for small and moderate-sized data sets. The inference is based on the per mutation of regressor residuals test introduced by Potter (2005). The implementation of glmperm outperforms currently available permutation test software as glmperm can be applied in situations where more than one covariate is involved.