Journal of Statistical Software http://www.jstatsoft.org/rss Wed, 30 Jul 2014 19:11:38 GMT Wed, 30 Jul 2014 19:11:38 GMT Most recent publications from the Journal of Statistical Software Regularization Paths for Conditional Logistic Regression: The clogitL1 Package http://www.jstatsoft.org/v58/i12/paper Vol. 58, Issue 12, Jul 2014

Abstract:

We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso ("1) and elastic net penalties. The sequential strong rules of Tibshirani, Bien, Hastie, Friedman, Taylor, Simon, and Tibshirani (2012) are also used in the algorithm and it is shown that these offer a considerable speed up over the standard coordinate descent algorithm with warm starts.

Once implemented, the algorithm is used in simulation studies to compare the variable selection and prediction performance of the conditional logistic regression model against that of its unconditional (standard) counterpart. We find that the conditional model performs admirably on datasets drawn from a suitable conditional distribution, outperforming its unconditional counterpart at variable selection. The conditional model is also fit to a small real world dataset, demonstrating how we obtain regularization paths for the parameters of the model and how we apply cross validation for this method where natural unconditional prediction rules are hard to come by.

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Sat, 05 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i12
Optimal Asset Pricing http://www.jstatsoft.org/v58/i11/paper Vol. 58, Issue 11, Jul 2014

Abstract:

We describe an R package for determining the optimal price of an asset which is “perishable” in a certain sense, given the intensity of customer arrivals and a time-varying price sensitivity function which specifies the probability that a customer will purchase an asset offered at a given price at a given time. The package deals with the case of customers arriving in groups, with a probability distribution for the group size being specified. The methodology and software allow for both discrete and continuous pricing. The class of possible models for price sensitivity functions is very wide, and includes piecewise linear models. A mechanism for constructing piecewise linear price sensitivity functions is provided.

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Sat, 05 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i11
movMF: An R Package for Fitting Mixtures of von Mises-Fisher Distributions http://www.jstatsoft.org/v58/i10/paper Vol. 58, Issue 10, Jul 2014

Abstract:

Finite mixtures of von Mises-Fisher distributions allow to apply model-based clustering methods to data which is of standardized length, i.e., all data points lie on the unit sphere. The R package movMF contains functionality to draw samples from finite mixtures of von Mises-Fisher distributions and to fit these models using the expectation-maximization algorithm for maximum likelihood estimation. Special features are the possibility to use sparse matrix representations for the input data, different variants of the expectation-maximization algorithm, different methods for determining the concentration parameters in the M-step and to impose constraints on the concentration parameters over the components.

In this paper we describe the main fitting function of the package and illustrate its application. In addition we compare the clustering performance of finite mixtures of von Mises-Fisher distributions to spherical k-means. We also discuss the resolution of several numerical issues which occur for estimating the concentration parameters and for determining the normalizing constant of the von Mises-Fisher distribution.

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Sat, 05 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i10
Statistical Software (R, SAS, SPSS, and Minitab) for Blind Students and Practitioners http://www.jstatsoft.org/v58/s01/paper Vol. 58, Software Review 1, Jul 2014

Statistical Software (R, SAS, SPSS, and Minitab) for Blind Students and Practitioners, version varies
R, SAS, SPSS, and Minitab

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Tue, 01 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/s01
Growth Curve Analysis and Visualization Using R http://www.jstatsoft.org/v58/b02/paper Vol. 58, Book Review 2, Jul 2014

Growth Curve Analysis and Visualization Using R
Daniel Mirman
Chapman & Hall/CRC, 2014
ISBN: 9781466584327

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Tue, 01 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/b02
Analyzing Spatial Models of Choice and Judgment with R http://www.jstatsoft.org/v58/b01/paper Vol. 58, Book Review 1, Jul 2014

Analyzing Spatial Models of Choice and Judgment with R
David A. Armstrong III, Ryan Bakker, Royce Carroll, Christopher Hare, Keith T. Poole, Howard Rosenthal
CRC Press, 2014
ISBN: 978-14665-1715-8

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Tue, 01 Jul 2014 07:00:00 GMT http://www.jstatsoft.org/v58/b01
copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas http://www.jstatsoft.org/v58/i09/paper Vol. 58, Issue 9, Jun 2014

Abstract:

The use of copula-based models in EDAs (estimation of distribution algorithms) is currently an active area of research. In this context, the copulaedas package for R provides a platform where EDAs based on copulas can be implemented and studied. The package offers complete implementations of various EDAs based on copulas and vines, a group of well-known optimization problems, and utility functions to study the performance of the algorithms. Newly developed EDAs can be easily integrated into the package by extending an S 4 class with generic functions for their main components. This paper presents copulaedas by providing an overview of EDAs based on copulas, a description of the implementation of the package, and an illustration of its use through examples. The examples include running the EDAs defined in the package, implementing new algorithms, and performing an empirical study to compare the behavior of different algorithms on benchmark functions and a real-world problem.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i09
%HPGLIMMIX: A High-Performance SAS Macro for GLMM Estimation http://www.jstatsoft.org/v58/i08/paper Vol. 58, Issue 8, Jun 2014

Abstract:

Generalized linear mixed models (GLMMs) comprise a class of widely used statistical tools for data analysis with fixed and random effects when the response variable has a conditional distribution in the exponential family. GLMM analysis also has a close relationship with actuarial credibility theory. While readily available programs such as the GLIMMIX procedure in SAS and the lme4 package in R are powerful tools for using this class of models, these progarms are not able to handle models with thousands of levels of fixed and random effects. By using sparse-matrix and other high performance techniques, procedures such as HPMIXED in SAS can easily fit models with thousands of factor levels, but only for normally distributed response variables. In this paper, we present the %HPGLIMMIX SAS macro that fits GLMMs with large number of sparsely populated design matrices using the doubly-iterative linearization (pseudo-likelihood) method, in which the sparse-matrix-based HPMIXED is used for the inner iterations with the pseudo-variable constructed from the inverse-link function and the chosen model. Although the macro does not have the full functionality of the GLIMMIX procedure, time and memory savings can be large with the new macro. In applications in which design matrices contain many zeros and there are hundreds or thousands of factor levels, models can be fitted without exhausting computer memory, and 90% or better reduction in running time can be observed. Examples with a Poisson, binomial, and gamma conditional distribution are presented to demonstrate the usage and efficiency of this macro.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i08
conting: An R Package for Bayesian Analysis of Complete and Incomplete Contingency Tables http://www.jstatsoft.org/v58/i07/paper Vol. 58, Issue 7, Jun 2014

Abstract:

The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete and incomplete contingency tables using hierarchical log-linear models. This package allows a user to identify interactions between categorical factors (via complete contingency tables) and to estimate closed population sizes using capture-recapture studies (via incomplete contingency tables). The models are fitted using Markov chain Monte Carlo methods. In particular, implementations of the Metropolis-Hastings and reversible jump algorithms appropriate for log-linear models are employed. The conting package is demonstrated on four real examples.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i07
KernSmoothIRT: An R Package for Kernel Smoothing in Item Response Theory http://www.jstatsoft.org/v58/i06/paper Vol. 58, Issue 6, Jun 2014

Abstract:

Item response theory (IRT) models are a class of statistical models used to describe the response behaviors of individuals to a set of items having a certain number of options. They are adopted by researchers in social science, particularly in the analysis of performance or attitudinal data, in psychology, education, medicine, marketing and other fields where the aim is to measure latent constructs. Most IRT analyses use parametric models that rely on assumptions that often are not satisfied. In such cases, a nonparametric approach might be preferable; nevertheless, there are not many software implementations allowing to use that.

To address this gap, this paper presents the R package KernSmoothIRT . It implements kernel smoothing for the estimation of option characteristic curves, and adds several plotting and analytical tools to evaluate the whole test/questionnaire, the items, and the subjects. In order to show the package's capabilities, two real datasets are used, one employing multiple-choice responses, and the other scaled responses.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i06
Smoothing Spline ANOVA Models: R Package gss http://www.jstatsoft.org/v58/i05/paper Vol. 58, Issue 5, Jun 2014

Abstract:

This document provides a brief introduction to the R package gss for nonparametric statistical modeling in a variety of problem settings including regression, density estimation, and hazard estimation. Functional ANOVA (analysis of variance) decompositions are built into models on product domains, and modeling and inferential tools are provided for tasks such as interval estimates, the “testing” of negligible model terms, the handling of correlated data, etc. The methodological background is outlined, and data analysis is illustrated using real-data examples.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i05
Hierarchical Archimedean Copulae: The HAC Package http://www.jstatsoft.org/v58/i04/paper Vol. 58, Issue 4, Jun 2014

Abstract:

This paper presents the R package HAC, which provides user friendly methods for dealing with hierarchical Archimedean copulae (HAC). Computationally efficient estimation procedures allow to recover the structure and the parameters of HAC from data. In addition, arbitrary HAC can be constructed to sample random vectors and to compute the values of the corresponding cumulative distribution plus density functions. Accurate graphics of the HAC structure can be produced by the plot method implemented for these objects.

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Mon, 30 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i04
changepoint: An R Package for Changepoint Analysis http://www.jstatsoft.org/v58/i03/paper Vol. 58, Issue 3, Jun 2014

Abstract:

One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has been developed to provide users with a choice of multiple changepoint search methods to use in conjunction with a given changepoint method and in particular provides an implementation of the recently proposed PELT algorithm. This article describes the search methods which are implemented in the package as well as some of the available test statistics whilst highlighting their application with simulated and practical examples. Particular emphasis is placed on the PELT algorithm and how results differ from the binary segmentation approach.

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Wed, 25 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i03
R Marries NetLogo: Introduction to the RNetLogo Package http://www.jstatsoft.org/v58/i02/paper Vol. 58, Issue 2, Jun 2014

Abstract:

The RNetLogo package delivers an interface to embed the agent-based modeling platform NetLogo into the R environment with headless (no graphical user interface) or interactive GUI mode. It provides functions to load models, execute commands, push values, and to get values from NetLogo reporters. Such a seamless integration of a widely used agent-based modeling platform with a well-known statistical computing and graphics environment opens up various possibilities. For example, it enables the modeler to design simulation experiments, store simulation results, and analyze simulation output in a more systematic way. It can therefore help close the gaps in agent-based modeling regarding standards of description and analysis. After a short overview of the agent-based modeling approach and the software used here, the paper delivers a step-by-step introduction to the usage of the RNetLogo package by examples.

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Wed, 25 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i02
Flexible Generation of E-Learning Exams in R: Moodle Quizzes, OLAT Assessments, and Beyond http://www.jstatsoft.org/v58/i01/paper Vol. 58, Issue 1, Jun 2014

Abstract:

The capabilities of the package exams for automatic generation of (statistical) exams in R are extended by adding support for learning management systems: As in earlier versions of the package exam generation is still based on separate Sweave files for each exercise " but rather than just producing different types of PDF output files, the package can now render the same exercises into a wide variety of output formats. These include HTML (with various options for displaying mathematical content) and XML specifications for online exams in learning management systems such as Moodle or OLAT. This flexibility is accomplished by a new modular and extensible design of the package that allows for reading all weaved exercises into R and managing associated supplementary files (such as graphics or data files). The manuscript discusses the readily available user interfaces, the design of the underlying infrastructure, and how new functionality can be built on top of the existing tools.

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Wed, 25 Jun 2014 07:00:00 GMT http://www.jstatsoft.org/v58/i01