Computer Sciences Commons^™

News From The Bioconductor Project, The Bioconductor Team

The R Journal

The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. The 934 software packages available in Bioconductor can be viewed at http://bioconductor.org/packages/release/. 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 and R version 3.1

Changes In R, The R Core Team

The R Journal

CHANGES IN 3.1.2

R Foundation News, Martin Mächler, Kurt Hornik

The R Journal

New R Foundation board

New ordinary members

Donations and new supporting members

Conference Report Polish Academic R User Meeting, Maciej Beręsewicz, Alicja Szabelska, Joanna Zyprych-Walczak, Łukasz Wawrowski

The R Journal

The first national conference “Polish Academic R User Meeting” (PAZUR) was held at the Poznan University of Economics from October 15–17, 2014. The organizers of the conference were the Department of Statistics at the Poznan University of Economics (PUE), the Department of Mathematical and Statistical Methods at the Poznan University of Life Sciences (PULS) and SKN Estymator, the students scientific association that resides at the Department of Statistics at the Poznan University of Economics. The honorary patronage of the conference took Professor Emil Panek, Dean of the Faculty of Informatics and Electronic Economy PUE and Professor Wiesław Koziara, Dean of …

Conference Report: R In Insurance 2014, Markus Gesmann, Andreas Tsanakas

The R Journal

The 2nd Rin Insurance conference took place at Cass Business School London on 14 July 2014. This one-day conference focused once more on the wide range of applications of Rin insurance, actuarial science and beyond. The conference programme covered topics including reserving, pricing, loss modelling, the use of R in a production environment and muchmore.

Qmethod: A Package To Explore Human Perspectives Using Q Methodology, Aiora Zabala

The R Journal

Q is a methodology to explore the distinct subjective perspectives that exist within a group. It is used increasingly across disciplines. The methodology is semi-qualitative and the data are analysed using data reduction methods to discern the existing patterns of thought. This package is the first to perform Q analysis in R, and it provides many advantages to the existing software: namely, it is fully cross-platform, the algorithms can be transparently examined, it provides results in a clearly structured and tabulated form ready for further exploration and modelling, it produces a graphical summary of the results, and it generates a …

Farewell's Linear Increments Model For Missing Data: The Flim Package, Rune Hoff, Jon Michael Gran, Daniel Farewell

The R Journal

Missing data is common in longitudinal studies. We present a package for Farewell’s Linear Increments Model for Missing Data (the FLIM package), which can be used to fit linear models for observed increments of longitudinal processes and impute missing data. The method is valid for data with regular observation patterns. The end result is a list of fitted models and a hypothetical complete dataset corresponding to the data we might have observed had individuals not been missing. The FLIM package may also be applied to longitudinal studies for causal analysis, by considering counterfactual data as missing data- for instance to …

Smr: An R Package For Computing The Externally Studentized Normal Midrange Distribution, Ben Dêivide, Oliveira Batista, Daniel Furtado Ferreira

The R Journal

The main purpose of this paper is to present the main algorithms underlining the con struction and implementation of the SMR package, whose aim is to compute studentized normal midrange distribution. Details on the externally studentized normal midrange and standardized normal midrange distributions are also given. The package follows the same structure as the prob ability functions implemented in R. That is: the probability density function (dSMR), the cumulative distribution function (pSMR), the quantile function (qSMR) and the random number generating function (rSMR). Pseudocode and illustrative examples of how to use the package are presented.

Sgof: An R Package For Multiple Testing Problems, Irene Castro-Conde, Jacob De Uña-Álvarez

The R Journal

In this paper we present a new R package called sgof for multiple hypothesis testing. The principal aim of this package is to implement SGoF-type multiple testing methods, known to be more powerful than the classical false discovery rate (FDR) and family-wise error rate (FWER) based methods in certain situations, particularly when the number of tests is large. This package includes Bi nomial and Conservative SGoF and the Bayesian and Beta-Binomial SGoF multiple testing procedures, which are adaptations of the original SGoF method to the Bayesian setting and to possibly correlated tests, respectively. The sgof package also implements the Benjamini-Hochberg …

Flexible R Functions For Processing Accelerometer Data, With Emphasis On Nhanes 2003–2006, Dane R. Van Domelen, W. Stephen Pittard

The R Journal

Accelerometers are a valuable tool for measuring physical activity (PA) in epidemiological studies. However, considerable processing is needed to convert time-series accelerometer data into meaningful variables for statistical analysis. This article describes two recently developed R packages for processing accelerometer data. The package accelerometry contains functions for performing various data processing procedures, such as identifying periods of non-wear time and bouts of activity. The functions are flexible, computationally efficient, and compatible with uniaxial or triaxial data. The package nhanesaccel is specifically for processing data from the National Health and Nutrition Examination Survey (NHANES), years 2003–2006. Its primary function generates measures …

Automatic Conversion Of Tables To Longform Dataframes, Jimmy Oh

The R Journal

TableToLongForm automatically converts hierarchical Tables intended for a human reader into a simple LongForm dataframe that is machine readable, making it easier to access and use the data for analysis. It does this by recognising positional cues present in the hierarchical Table (which would normally be interpreted visually by the human brain) to decompose, then reconstruct the data into a LongForm dataframe. The article motivates the benefit of such a conversion with an example Table, followed by a short user manual, which includes a comparison between the simple one argument call to TableToLongForm, with code for an equivalent manual conversion. …

Gset: An R Package For Exact Sequential Test Of Equivalence Hypothesis Based On Bivariate Non-Central T-Statistics, Fang Liu

The R Journal

The R package gset calculates equivalence and futility boundaries based on the exact bivariate non-central t test statistics. It is the first R package that targets specifically at the group sequential test of equivalence hypotheses. The exact test approach adopted by gset neither assumes the large-sample normality of the test statistics nor ignores the contribution to the overall Type I error rate from rejecting one out of the two one-sided hypotheses under a null value. The features of gset include: error spending functions, computation of equivalence boundaries and futility boundaries, either binding or nonbinding, depiction of stagewise boundary plots, and …

Editorial, Deepayan Sarkar

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 6, Issue 2 of the R Journal.

Mvn: An R Package For Assessing Multivariate Normality, Selcuk Korkmaz, Dincer Goksuluk, Gokmen Zararsiz

The R Journal

Assessing the assumption of multivariate normality is required by many parametric multivariate statistical methods, such as MANOVA, linear discriminant analysis, principal component analysis, canonical correlation, etc. It is important to assess multivariate normality in order to proceed with such statistical methods. There are many analytical methods proposed for checking multivariate normality. However, deciding which method to use is a challenging process, since each method may give different results under certain conditions. Hence, we may say that there is no best method, which is valid under any condition, for normality checking. In addition to numerical results, it is very useful to …

Ngspatial: A Package For Fitting The Centered Autologistic And Sparse Spatial Generalized Linear Mixed Models For Areal Data, John Hughes

The R Journal

Two important recent advances in areal modeling are the centered autologistic model and the sparse spatial generalized linear mixed model (SGLMM), both of which are reparameterizations of traditional models. The reparameterizations improve regression inference by alleviating spatial confounding, and the sparse SGLMM also greatly speeds computing by reducing the dimension of the spatial random effects. Package ngspatial (’ng’ = non-Gaussian) provides routines for fitting these new models. The package supports composite likelihood and Bayesian inference for the centered autologistic model, and Bayesian inference for the sparse SGLMM.

Coordinate-Based Meta-Analysis Of Fmri Studies With R, Andrea Stocco

The R Journal

This paper outlines how to conduct a simple meta-analysis of neuroimaging foci of activation in R. In particular, the first part of this paper reviews the nature of fMRI data, and presents a brief overview of the existing packages that can be used to analyze fMRI data in R. The second part illustrates how to handle fMRI data by showing how to visualize the results of different neuroimaging studies in a so-called orthographic view, where the spatial distribution of the foci of activation from different fMRI studies can be inspected visually.

Functional MRI (fMRI) is one of the most important …

Bshazard: A Flexible Tool For Nonparametric Smoothing Of The Hazard Function, Paola Rebora, Agus Salim, Marie Reilly

The R Journal

The hazard function is a key component in the inferential process in survival analysis and relevant for describing the pattern of failures. However, it is rarely shown in research papers due to the difficulties in nonparametric estimation. We developed the bshazard package to facilitate the computation of a nonparametric estimate of the hazard function, with data-driven smoothing. The method accounts for left truncation, right censoring and possible covariates. B-splines are used to estimate the shape of the hazard within the generalized linear mixed models frame work. Smoothness is controlled by imposing an autoregressive structure on the baseline hazard coefficients. This …

Prinsimp, Jonathan Zhang, Nancy Heckman, Davor Cubranic, Joel G. Kingsolver, Travis Gaydos, J.S. Marron

The R Journal

Principal Components Analysis (PCA) is a common way to study the sources of variation in a high-dimensional data set. Typically, the leading principal components are used to understand the variation in the data or to reduce the dimension of the data for subsequent analysis. The remaining principal components are ignored since they explain little of the variation in the data. However, the space spanned by the low variation principal components may contain interesting structure, structure that PCA cannot find. Prinsimp is an R package that looks for interesting structure of low variability. “Interesting” is defined in terms of a simplicity …

Phaser: An R Package For Phase Plane Analysis Of Autonomous Ode Systems, Michael J. Grayling

The R Journal

When modelling physical systems, analysts will frequently be confronted by differential equations which cannot be solved analytically. In this instance, numerical integration will usually be the only way forward. However, for autonomous systems of ordinary differential equations (ODEs) in one or two dimensions, it is possible to employ an instructive qualitative analysis foregoing this requirement, using so-called phase plane methods. Moreover, this qualitative analysis can even prove to be highly useful for systems that can be solved analytically, or will be solved numerically anyway. The package phaseR allows the user to perform such phase plane analyses: determining the stability of …

Taming Pitchf/X Data With Xml2r And Pitchrx, Carson Sievert

The R Journal

XML2R is a framework that reduces the effort required to transform XML content into tables in a way that preserves parent to child relationships. pitchRx applies XML2R’s grammar for XML manipulation to Major League Baseball Advanced Media (MLBAM)’s Gameday data. With pitchRx, one can easily obtain and store Gameday data in a remote database. The Gameday website hosts a wealth of XML data, but perhaps most interesting is PITCHf/x. Among other things, PITCHf/x data can be used to recreate a baseball’s flight path from a pitcher’s hand to home plate. With pitchRx, one can easily create animations …

Applying Spartan To Understand Parameter Uncertainty In Simulations, Kieran Alden, Mark Read, Paul S. Andrews, Jon Timmis, Mark Coles

The R Journal

In attempts to further understand the dynamics of complex systems, the application of computer simulation is becoming increasingly prevalent. Whereas a great deal of focus has been placed in the development of software tools that aid researchers develop simulations, similar focus has not been applied in the creation of tools that perform a rigorous statistical analysis of results generated through simulation: vital in understanding how these results offer an insight into the captured system. This encouraged us to develop spartan, a package of statistical techniques designed to assist researchers in understanding the relationship between their simulation and the real system. …

The R Journal (December 2014) 6(2): Complete Issue, The R Foundation

The R Journal

Editorial, Deepayan Sarkar

Contributed Research Articles

Coordinate-Based Meta-Analysis of fMRI Studies with R, Andrea Stocco

Automatic Conversion of Tables to LongForm Dataframes, Jimmy Oh

Prinsimp, Jonathan Zhang, Nancy Heckman, Davor Cubranic, Joel G. Kingsolver, Travis Gaydos, and J. S. Marron

phaseR: An R Package for Phase Plane Analysis of Autonomous ODE Systems, Michael J. Grayling

Flexible R Functions for Processing Accelerometer Data, with Emphasis on NHANES 2003-2006, Dane R. Van Domelen and W. Stephen Pittard

Applying spartan to Understand Parameter Uncertainty in Simulations, Kieran Alden, Mark Read, Paul S. Andrews, Jon Timmis, and Mark Coles

ngspatial: A Package for Fitting …

Study Of Parallel Programming Models On Computer Clusters With Accelerators, Chenggang Lai

Graduate Theses and Dissertations

In order to reach exascale computing capability, accelerators have become a crucial part in developing supercomputers. This work examines the potential of two latest acceleration technologies, Intel Many Integrated Core (MIC) Architecture and Graphics Processing Units (GPUs). This thesis applies three benchmarks under 3 different configurations, MPI+CPU, MPI+GPU, and MPI+MIC. The benchmarks include intensely communicating application, loosely communicating application, and embarrassingly parallel application. This thesis also carries out a detailed study on the scalability and performance of MIC processors under two programming models, i.e., offload model and native model, on the Beacon computer cluster.

According to different benchmarks, the results …

Alternative Approaches To Correction Of Malapropisms In Aiml Based Conversational Agents, Walter A. Brock

CCAC Theses and Dissertations

The use of Conversational Agents (CAs) utilizing Artificial Intelligence Markup Language (AIML) has been studied in a number of disciplines. Previous research has shown a great deal of promise. It has also documented significant limitations in the abilities of these CAs. Many of these limitations are related specifically to the method employed by AIML to resolve ambiguities in the meaning and context of words. While methods exist to detect and correct common errors in spelling and grammar of sentences and queries submitted by a user, one class of input error that is particularly difficult to detect and correct is the …

Web Application Vulnerability Prediction Using Hybrid Program Analysis And Machine Learning, Lwin Khin Shar, Lionel Briand, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Due to limited time and resources, web software engineers need support in identifying vulnerable code. A practical approach to predicting vulnerable code would enable them to prioritize security auditing efforts. In this paper, we propose using a set of hybrid (staticþdynamic) code attributes that characterize input validation and input sanitization code patterns and are expected to be significant indicators of web application vulnerabilities. Because static and dynamic program analyses complement each other, both techniques are used to extract the proposed attributes in an accurate and scalable way. Current vulnerability prediction techniques rely on the availability of data labeled with vulnerability …

A Catalog Of While Loop Specification Patterns, Aditi Barua, Yoonsik Cheon

Departmental Technical Reports (CS)

This document provides a catalog of while loop patterns along with their skeletal specifications. The specifications are written in a functional form known as intended functions. The catalog can be used to derive specifications of while loops by first matching the loops to the cataloged patterns and then instantiating the skeletal specifications of the matched patterns. Once their specifications are formulated and written, the correctness of while loops can be proved rigorously or formally using the functional program verification technique in which a program is viewed as a mathematical function from one program state to another.

Safe Zero-Cost Coercions For Haskell, Joachim Breitner, Richard A. Eisenberg, Simon Peyton Jones, Stephanie Weirich

Computer Science Faculty Research and Scholarship

Generative type abstractions – present in Haskell, OCaml, and other languages – are useful concepts to help prevent programmer errors. They serve to create new types that are distinct at compile time but share a run-time representation with some base type. We present a new mechanism that allows for zero-cost conversions between generative type abstractions and their representations, even when such types are deeply nested. We prove type safety in the presence of these conversions and have implemented our work in GHC.

Event Analytics, Jin Song Dong, Jun Sun, Yang Liu, Yuan-Fang Li

Research Collection School Of Computing and Information Systems

The process analysis toolkit (PAT) integrates the expressiveness of state, event, time, and probability-based languages with the power of model checking. PAT is a self-contained reasoning system for system specification, simulation, and verification. PAT currently supports a wide range of 12 different expressive modeling languages with many application domains and has attracted thousands of registered users from hundreds of organizations. In this invited talk, we will present the PAT system and its vision on “Event Analytics” (EA) which is beyond “Data Analytics”. The EA research is based on applying model checking to event planning, scheduling, prediction, strategy analysis and decision …

Applying Genetic Programming To Bytecode And Assembly, Eric Collom

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Traditional genetic programming (GP) is typically not used to perform unrestricted evolution on entire programs at the source code level. Instead, only small sections within programs are usually evolved. Not being able to evolve whole programs is an issue since it limits the flexibility of what can be evolved. Evolving programs in either bytecode or assembly language is a method that has been used to perform unrestricted evolution. This paper provides an overview of applying genetic programming to Java bytecode and x86 assembly. Two examples of how this method has been implemented will be explored. We will also discuss experimental …

An Overview Of The Current State Of The Test-First Vs. Test-Last Debate, Christopher M. Thomas

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

When it comes to software development, perhaps one of the most important and time consuming processes is that of software testing. In fact, early studies on software testing estimated that it could consume fifty percent or more of development costs for a product. Because of this, the ability to optimize testing to reduce testing costs can be very valuable. In this paper we compare two popular methods, test-last testing, often used in waterfall software development processes, and test-first testing, often used in Agile test driven software development methods, by reviewing recent studies on the subject. In this review we discuss …