Numerical Analysis and Scientific Computing Commons^™

The R Journal (December 2013) 5(2): Complete Issue, The R Foundation

The R Journal

Editorial, Hadley Wickham

Contributed Research Articles

factorplot: Improving Presentation of Simple Contrasts in Generalized Linear Models, David A. Armstrong II

spMC: Modelling Spatial Random Fields with Continuous Lag Markov Chains, Luca Sartore

RNetCDF: A Package for Reading and Writing NetCDF Datasets, Pavel Michna and Milton Woods

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

Performance Attribution for Equity Portfolios, Yang Lu and David Kane

ExactCIdiff: An R Package for Computing Exact Confidence Intervals for the Difference of Two Proportions, Guogen Shan and Weizhen Wang

rlme: An R Package for Rank-Based Estimation and Prediction in Random …

Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade

CBN Journal of Applied Statistics (JAS)

Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …

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. …

Reconstructing Point Clouds Of Mid-Size Objects, Spencer Woodworth

Computer Science and Software Engineering

This project explores the use of an inexpensive 3D camera for the acquisition and reconstruction of mid-size objects. The disparity of objects between stereo image pairs are used to calculate depth and generate a depth map. The depth map is used to generate a point cloud representation of the object from a single view. Finally, point clouds are generated from several views of an object and then aligned and merged into a seamless 360-degree point cloud.

Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh

Research Collection School Of Computing and Information Systems

Increase in the frequency of disruptions in the recent times and their impact have increased the attention in supply chain disruption management research. The objective of this paper is to understand as to how a disruption might affect the supply chain network - depending upon the network structure, the node that is disrupted, the disruption in production capacity of the disrupted node and the period of the disruption - via decision trees. To this end, we first developed a 5-tier agent-based supply chain model and then simulated it for various what-if disruptive scenarios for 3 different network structures (80 trials …

The Influence Of Online Word-Of-Mouth On Long Tail Formation, Bin Gu, Qian Tang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

The long tail phenomenon has been attributed to both supply side and demand side economies. While the cause on the supply side is well-known, research on the demand side has largely focused on the awareness effect of online information that helps consumers discover new and often niche products. This study expands the demand side factors by showing that online information also influences the long tail phenomenon through the informative effect, which affects consumers' evaluation of product quality. We examine the informative effect in the context of online WOM. Two sets of theories suggest opposite directions for the implication of the …

An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams

CBN Journal of Applied Statistics (JAS)

This paper proposed an efficient two sample capture-recapture model (Ma) with high recaptures and compared it with the existing models like the model of no factor effect (Mo), behavioral response model (Mb) and the Petersen model (Ms), using simulated data. We found that the Petersen model provides a better estimate of the population size when the observations follow a hypergeometric distribution and the population is overestimated when recapture is high. It was also found that the proposed model provides a better estimator of the population size than the existing ones when the recapture is high. This model is particularly useful …

Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair

CBN Journal of Applied Statistics (JAS)

This paper uses Johansen’s cointegration to test for the possibility of cointegration and Granger-causality to estimate the causal relationship between stock market index and monetary indicators (exchange rate and M2) before and during the global financial crisis for Nigeria, using monthly data for the period 2001–2011. Results suggest absence of long-run relationship before and during the crisis. The Granger-causality tests show a uni-directional causality running from M2 to ASI before the crisis while during the period of the crisis there is absence of causality between the variables. This suggests that ASI show responsiveness to M2. Thus, absence of the direct …

Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo

CBN Journal of Applied Statistics (JAS)

This paper investigates chaos in a Nigerian mutual fund, Asset and Resource Management Company Limited (ARM) for a period of eleven years. The existence of chaotic signals in the data was identified by the reconstruction of the phase space of the daily closing price of the fund and the delay time was quantified using mutual information function and the embedding dimension by the false nearest neighbours, where the values were identified to be 15 and 20 respectively. The presence of chaotic signals in the ARM data was further confirmed by the correlation dimension method which yielded a dimension of 2.2 …

Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete

CBN Journal of Applied Statistics (JAS)

This work considers the application of Periodogram and Fourier Series Analysis to model all-items monthly inflation rates in Nigeria from 2003 to 2011. The main objectives are to identify inflation cycles, fit a suitable model to the data and make forecasts of future values. To achieve these objectives, monthly all-items inflation rates for the period were obtained from the Central Bank of Nigeria (CBN) website. Periodogram and Fourier series methods of analysis are used to analyze the data. Based on the analysis, it was found that inflation cycle within the period was fifty one (51) months, which coincides with the …