Computer Sciences Commons^™

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

New CRAN task views

New packages in CRAN task views

New contributed packages

Other changes

Conference Report: Deuxièmes Rencontres R, Aurelie Siberchicot, Stephane Dray

The R Journal

Following the success of the first "Rencontres R" (Bordeaux, 2-3 July 2012, http://r2012. bordeaux.inria.fr/), the second meeting was held in Lyon on 27-28 June 2013. This French speaking conference was a great success with 216 participants (110 were present at the first conference). The aim of the meeting was to provide a national forum for the exchange and sharing of ideas on the use of R in different disciplines. The number of participants and the list of sponsors (http://r2013-lyon.sciencesconf.org/resource/sponsors) demonstrate the increasing impact of R in both industry and academia in France. The program, detailed below, consisted of plenary sessions, …

News From The Bioconductor Project, Bioconductor Team

The R Journal

Bioconductor 2.13 was released on 15 October2013. It is compatible with R3.0.2, and consists of 749 software packages, 179 experiment data packages, and more than 690 up-to-date annotation packages. The release includes 84 new software packages, and enhancements to many others. Descriptions of new packages and updated NEWS files provided by current package maintainers are at http://bioconductor.org/news/bioc_2_13_release/

Complognormal: An R Package For Composite Lognormal Distributions, S. Nadarajah, S. A.A. Bakar

The R Journal

In recent years, composite models based on the lognormal distribution have become popular in actuarial sciences and related areas. In this short note, we present a new R package for computing the probability density function, cumulative density function, and quantile function, and for generating random numbersof anycomposite model based on the lognormal distribution. The use of the package is illustrated using a real data set.

Dynamic Parallelization Of R Functions, Stefan Böhringer

The R Journal

R offers several extension packages that allow it to perform parallel computations. These operate on fixed points in the program flow and make it difficult to deal with nested parallelism and to organize parallelism in complex computations in general. In this article we discuss, first, of how to detect parallelism in functions, and second, how to minimize user intervention in that process. We present a solution that requires minimal code changes and enables to flexibly and dynamically choose the degree of parallelization in the resulting computation. An implementation is provided by the R package parallelize.dynamic and practical issues are discussed …

Surface Melting Curve Analysis With R, Stefan Rödiger, Alexander Böhm, Ingolf Schimke

The R Journal

Nucleic acid Melting Curve Analysis is a powerful method to investigate the interaction of double stranded nucleic acids. Many researchers rely on closed source software which is not ubiquitously available, and gives only little control over the computation and data presentation. R in contrast, is open source, highly adaptable and provides numerous utilities for data import, sophisticated statistical analysis and presentation in publication quality. This article covers methods, implemented in the MBmca package, for DNA Melting Curve Analysis on microbead surfaces. Particularly, the use of the second derivative melting peaks is suggested as an additional parameter to characterize the melting …

Factorplot: Improving Presentation Of Simple Contrasts In Generalized Linear Models, David A. Armstrong Ii

The R Journal

Recent statistical literature has paid attention to the presentation of pairwise comparisons either from the point of view of the reference category problem in generalized linear models (GLMs) or in terms of multiple comparisons. Both schools of thought are interested in the parsimonious presentation of sufficient information to enable readers to evaluate the significance of contrasts resulting from the inclusion of qualitative variables in GLMs. These comparisons also arise when trying to interpret multinomial models where one category of the dependent variable is omitted as a reference. While considerable advances have been made, opportunities remain to improve the presentation of …

Changes In R, The R Core Team

The R Journal

CHANGES IN R 3.0.2

R Foundation News, Kurt Hornik

The R Journal

Donations and new members

• Donations
• New supporting institutions
• New supporting members

The R In Robotics, André Dietrich, Sebastian Zug, Jörg Kaiser

The R Journal

The aim of this contribution is to connect two previously separated worlds: robotic application development with the Robot Operating System (ROS) and statistical programming with R. This fruitful combination becomes apparent especially in the analysis and visualization of sensory data. We therefore introduce a new language extension for ROS that allows to implement nodes in pure R. All relevant aspects are described in a step-by-step development of a common sensor data transformation node. This includes the reception of raw sensory data via the ROS network, message interpretation, bag-file analysis, transformation and visualization, as well as the transmission of newly generated …

Spmc: Modelling Spatial Random Fields With Continuous Lag Markov Chains, Luca Sartore

The R Journal

Currently, a part of the R statistical software is developed in order to deal with spatial models. More specifically, some available packages allow the user to analyse categorical spatial random patterns. However, only the spMC package considers a viewpoint based on transition probabilities between locations. Through the use of this package it is possible to analyse the spatial variability of data, make inference, predict and simulate the categorical classes in unobserved sites. An example is presented by analysing the well-known Swiss Jura data set.

Rlme: An R Package For Rank-Based Estimation And Prediction In Random Effects Nested Models, Yusuf K. Bilgic, Herbert Susmann

The R Journal

There is a lack of robust statistical analyses for random effects linear models. In practice, statistical analyses, including estimation, prediction and inference, are not reliable when data are unbalanced, of small size, contain outliers, or not normally distributed. It is fortunate that rank-based regression analysis is a robust nonparametric alternative to likelihood and least squares analysis. We propose an R package that calculates rank-based statistical analyses for two- and three-level random effects nested designs. In this package, a new algorithm which recursively obtains robust predictions for both scale and random effects is used, along with three rank-based fitting methods.

Performance Attribution For Equity Portfolios, Yang Lu, David Kane

The R Journal

The pa package provides tools for conducting performance attribution for long-only, single currency equity portfolios. The package uses two methods: the Brinson-Hood-Beebower model (hereafter referred to as the Brinson model) and a regression-based analysis. The Brinson model takes an ANOVA-type approach and decomposes the active return of any portfolio into asset allocation, stock selection, and interaction effect. The regression-based analysis utilizes estimated coefficients, based on a regression model, to attribute active return to different factors.

Temporal Disaggregation Of Time Series, Christoph Sax, Peter Steiner

The R Journal

Temporal disaggregation methods are used to disaggregate low frequency time series to higher frequency series, where either the sum, the average, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. The package tempdisagg is a collection of several methods for temporal disaggregation.

On Sampling From The Multivariate T Distribution, Marius Hofert

The R Journal

The multivariate normal and the multivariate t distributions belong to the most widely used multivariate distributions in statistics, quantitative risk management, and insurance. In contrast to the multivariate normal distribution, the parameterization of the multivariate t distribution does not correspond to its moments. This, paired with a non-standard implementation in the R package mvtnorm, provides traps for working with the multivariate t distribution. In this paper, common traps are clarified and corresponding recent changes to mvtnorm are presented.

Editorial, Hadley Wickham

The R Journal

Welcome to volume 5, issue 2 of The R Journal. I’m very pleased to include 21 articles about R for your enjoyment.

The end of the year also brings changes to the editorial board. Martyn Plummer is leaving the board after four years. Martyn was responsible for writing up the standard operating procedures for the journal, an act which has made my life as a new editor considerably easier! We welcome Michael Lawrence, who will join the editorial board in 2014. I am stepping down as Editor-in-Chief and will be leaving this task in the capable hands of Deepayan Sarkar.

Rnetcdf: A Package For Reading And Writing Netcdf Datasets, Pavel Michna, Milton Woods

The R Journal

This paper describes the RNetCDF package (version 1.6), an interface for reading and writing files in Unidata NetCDF format, and gives an introduction to the NetCDF file format. NetCDF is a machine independent binary file format which allows storage of different types of array based data, along with short metadata descriptions. The package presented here allows access to the most important functions of the NetCDF C-interface for reading, writing, and modifying NetCDF datasets. In this paper, we present a short overview on the NetCDF file format and show usage examples of the package.

Betategarch: Simulation, Estimation And Forecasting Of Beta-Skew-T-Egarch Models, Genaro Sucarrat

The R Journal

This paper illustrates the usage of the betategarch package, a package for the simulation, estimation and forecasting of Beta-Skew-t-EGARCH models. The Beta-Skew-t-EGARCH model is a dynamic model of the scale or volatility of financial returns. The model is characterised by its robustness to jumps or outliers, and by its exponential specification of volatility. The latter enables richer dynamics, since parameters need not be restricted to be positive to ensure positivity of volatility. In addition, the model also allows for heavy tails and skewness in the conditional return (i.e. scaled return), and for leverage and a time-varying long-term component in the …

Lfe: Linear Group Fixed Effects, Simen Gaure

The R Journal

Linear models with fixed effects and many dummy variables are common in some fields. Such models are straightforward to estimate unless the factors have too many levels. The R package lfe solves this problem by implementing a generalization of the within transformation to multiple factors, tailored for large problems.

Changes To Grid For R 3.0.0, Paul Murrell

The R Journal

From R 3.0.0, there is a new recommended way to develop new grob classes in grid. In a nutshell, two new “hook” functions, makeContext() and makeContent() have been added to grid to provide an alternative to the existing hook functions preDrawDetails(), drawDetails(), and postDrawDetails(). There is also a new function called grid.force(). This article discusses why these changes have been made, provides a simple demonstration of the use of the new functions, and discusses some of the implications for packages that build on grid.

Exactcidiff: An R Package For Computing Exact Confidence Intervals For The Difference Of Two Proportions, Guogen Shan, Weizhen Wang

The R Journal

Comparing two proportions through the difference is a basic problem in statistics and has applications in many fields. More than twenty confidence intervals (Newcombe, 1998a,b) have been proposed. Most of them are approximate intervals with an asymptotic infimum coverage probability much less than the nominal level. In addition, large sample may be costly in practice. So exact optimal confidence intervals become critical for drawing valid statistical inference with accuracy and precision. Recently, Wang (2010, 2012) derived the exact smallest (optimal) one-sided 1 confidence intervals for the difference of two paired or independent proportions. His intervals, however, are computer-intensive by nature. …

Clustering And Classification Of Multi-Domain Proteins, Neethu Shah

School of Computing: Dissertations, Theses, and Student Research

Rapid development of next-generation sequencing technology has led to an unprecedented growth in protein sequence data repositories over the last decade. Majority of these proteins lack structural and functional characterization. This necessitates design and development of fast, efficient, and sensitive computational tools and algorithms that can classify these proteins into functionally coherent groups.

Domains are fundamental units of protein structure and function. Multi-domain proteins are extremely complex as opposed to proteins that have single or no domains. They exhibit network-like complex evolutionary events such as domain shuffling, domain loss, and domain gain. These events therefore, cannot be represented in the …

Algorithms For Grid Graphs In The Mapreduce Model, Taylor P. Spangler

School of Computing: Dissertations, Theses, and Student Research

The MapReduce programming paradigm has seen widespread use in analyzing large data sets. Often these large data sets can be formulated as graphs. Many algorithms, such as filtering based algorithms, are designed to work efficiently for dense graphs - graphs with substantially more number of edges than the number of vertices. These algorithms are not optimized for sparse graphs - graphs where the number of edges is of the same order as the number of vertices. However, sparse graphs are also common in big data sets. In this thesis we present algorithms for maximal matching, approximate edge covering, and approximate …

Suddenly...I'M Consulting On Data Management Plans! Data Management Plan Consultant Checklist, Kiyomi D. Deards

University of Nebraska-Lincoln Libraries: Presentations

This webinar will outline the most important questions to ask, and the best resources available, for those who "suddenly" will be consulting on data management plans.

Articulatory Distinctiveness Of Vowels And Consonants: A Data-Driven Approach, Jun Wang, Jordan R. Green, Ashok Samal, Yana Yunusova

School of Computing: Faculty Publications

Purpose: To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.

Method: Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces …

Isptm: An Iterative Search Algorithm For Systematic Identification Of Post-Translational Modifications From Complex Proteome Mixtures, Xin Huang, Lin Huang, Hong Peng, Ashu Guru, Weihua Zue, Sang Yong Hong, Miao Liu, Seema Sharma, Kai Fu, Adam Caprez, David Swanson, Zhixin Zhang, Shi-Jian Ding

Holland Computing Center: Faculty Publications

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear …

Word Recognition From Continuous Articulatory Movement Time-Series Data Using Symbolic Representations, Jun Wang, Arvind Balasubramanian, Luis Mojica De La Vega, Jordan R. Green, Ashok Samal, Balakrishnan Prabhakaran

School of Computing: Conference and Workshop Papers

Although still in experimental stage, articulation-based silent speech interfaces may have significant potential for facilitating oral communication in persons with voice and speech problems. An articulation-based silent speech interface converts articulatory movement information to audible words. The complexity of speech production mechanism (e.g., co-articulation) makes the conversion a formidable problem. In this paper, we reported a novel, real-time algorithm for recognizing words from continuous articulatory movements. This approach differed from prior work in that (1) it focused on word-level, rather than phoneme-level; (2) online segmentation and recognition were conducted at the same time; and (3) a symbolic representation (SAX) was …

Automated Test Case Generation To Validate Non-Functional Software Requirements, Pingyu Zhang

School of Computing: Dissertations, Theses, and Student Research

A software system is bounded by a set of requirements. Functional requirements describe what the system must do, in terms of inputs, behavior, and outputs. We define non-functional requirements to be how well these functional requirements are satisfied, in terms of qualities or constraints on the design or on the implementation of a system. In practice, the validation of these kinds of requirements, does not receive equal emphasis. Techniques for validating functional requirements target all levels of software testing phases, and explore both black-box and white-box approaches. Techniques for validating non-functional requirements, on the other hand, largely operate in a …

Discovering Divergence: A Framework For Finding Unexpected Behavior Using Directed Exploration, Heath G. Roehr

School of Computing: Dissertations, Theses, and Student Research

Systems that are written to achieve the same high level specifications can vary in subtle ways. Depending on a programmer's objective, using one variant of a program or algorithm over another may be beneficial, and this objective may change over time. However we do not have sufficient techniques to compare two different system variants side-by-side to find specific behavioral differences, particularly in the absence of source code. Assuming two system implementations take the same inputs and produce the same outputs or exhibit the same behavior under most conditions, we want to find input instances where the behavior diverges for a …

Solving The Search For Source Code, Kathryn T. Stolee

School of Computing: Dissertations, Theses, and Student Research

Programmers frequently search for source code to reuse using keyword searches. When effective and efficient, a code search can boost programmer productivity, however, the search effectiveness depends on the programmer's ability to specify a query that captures how the desired code may have been implemented. Further, the results often include many irrelevant matches that must be filtered manually. More semantic search approaches could address these limitations, yet existing approaches either do not scale, are not flexible enough to find approximate matches, or require complex specifications.

We propose a novel approach to semantic search that addresses some of these limitations and …