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Easyroc: An Interactive Web-Tool For Roc Curve Analysis Using R Language Environment, Dincer Goksuluk, Selcuk Korkmaz, Gokmen Zararsiz, A Ergun Karaagaoglu 2016 Hacettepe University

Easyroc: An Interactive Web-Tool For Roc Curve Analysis Using R Language Environment, Dincer Goksuluk, Selcuk Korkmaz, Gokmen Zararsiz, A Ergun Karaagaoglu

The R Journal

ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls. There are a number of analysis tools which are used to guide researchers through their analysis. Some of these tools are commercial and provide basic methods for ROC curve analysis while others offer advanced analysis techniques and a command-based user interface, such as the R environment. The R environment includes comprehensive tools for ROC curve analysis; however, using a command-based interface might be challenging and time …


Variants Of Simple Correspondence Analysis, Rosaria Lombardo, Eric J. Beh 2016 University of Naples Campania “Luigi Vanvitelli”

Variants Of Simple Correspondence Analysis, Rosaria Lombardo, Eric J. Beh

The R Journal

This paper presents the R package CAvariants (Lombardo and Beh, 2017). The package performs six variants of correspondence analysis on a two-way contingency table. The main function that shares the same name as the package– CAvariants– allows the user to choose (via a series of input parameters) from six different correspondence analysis procedures. These include the classical approach to (symmetrical) correspondence analysis, singly ordered correspondence analysis, doubly ordered correspondence analysis, non symmetrical correspondence analysis, singly ordered non symmetrical correspondence analysis and doubly ordered non symmetrical correspondence analysis. The code provides the flexibility for constructing either a classical correspondence plot or …


Qtools: A Collection Of Models And Tools For Quantile Inference, Marco Geraci 2016 University of South Carolina

Qtools: A Collection Of Models And Tools For Quantile Inference, Marco Geraci

The R Journal

Quantiles play a fundamental role in statistics. The quantile function defines the distribution of a random variable and, thus, provides a way to describe the data that is specular but equivalent to that given by the corresponding cumulative distribution function. There are many advantages in working with quantiles, starting from their properties. The renewed interest in their usage seen in the last years is due to the theoretical, methodological, and software contributions that have broadened their applicability. This paper presents the R package Qtools, a collection of utilities for unconditional and conditional quantiles.


Rnrfa: An R Package To Retrieve, Filter And Visualize Data From The Uk National River Flow Archive, Claudia Vitolo, Matthew Fry, Wouter Buytaert 2016 European Centre for Medium-range Weather Forecast

Rnrfa: An R Package To Retrieve, Filter And Visualize Data From The Uk National River Flow Archive, Claudia Vitolo, Matthew Fry, Wouter Buytaert

The R Journal

The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment information. Data are served through the NRFA webservices via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for …


Eicompare: Comparing Ecological Inference Estimates Across Ei And Ei:Rc, Loren Collingwood, Kassra Oskooii, Sergio Garcia-Rios, Matt Barreto 2016 University of California, Riverside

Eicompare: Comparing Ecological Inference Estimates Across Ei And Ei:Rc, Loren Collingwood, Kassra Oskooii, Sergio Garcia-Rios, Matt Barreto

The R Journal

Social scientists and statisticians often use aggregate data to predict individual-level behavior because the latter are not always available. Various statistical techniques have been developed to make inferences from one level (e.g., precinct) to another level (e.g., individual voter) that minimize errors associated with ecological inference. While ecological inference has been shown to be highly problematic in a wide array of scientific fields, many political scientists and analysis employ the techniques when studying voting patterns. Indeed, federal voting rights lawsuits now require such an analysis, yet expert reports are not consistent in which type of ecological inference is used. This …


Qpot: An R Package For Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, Karen C. Abbott 2016 Case Western Reserve University

Qpot: An R Package For Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, Karen C. Abbott

The R Journal

QPot (pronounced ky oo + p¨ at) is an R package for analyzing two-dimensional systems of stochastic differential equations. It provides users with a wide range of tools to simulate, analyze, and visualize the dynamics of these systems. One of QPot’s key features is the computation of the quasi-potential, an important tool for studying stochastic systems. Quasi-potentials are particularly useful for comparing the relative stabilities of equilibria in systems with alternative stable states. This paper describes QPot’s primary functions, and explains how quasi-potentials can yield insights about the dynamics of stochastic systems. Three worked examples guide users through the application …


Editorial, Michael Lawrence 2016 R Project

Editorial, Michael Lawrence

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 8, Issue 2 of the R Journal. This issue contains 33 contributed research articles. Each of them either presents an R package, a specific extension of an R package or applications using R packages available from the Comprehensive R Archive Network (CRAN, http:://CRAN.R-project.org). This issue highlights the breadth and depth of the R package ecosystem, covering advances in statistical computing and visualization, as well as novel applications of R in specific domains. The authors have described a small but representative sample of the now more than 11000 packages …


R Foundation News, Torsten Hothorn 2016 Universität Zürich

R Foundation News, Torsten Hothorn

The R Journal

New benefectors

Donations

New supporting institutions

New supporting members


Subgroup Discovery With Evolutionary Fuzzy Systems In R: The Sdefsr Package, Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María J. del Jesus 2016 University of Jaén

Subgroup Discovery With Evolutionary Fuzzy Systems In R: The Sdefsr Package, Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María J. Del Jesus

The R Journal

Subgroup discovery is a data mining task halfway between descriptive and predictive data mining. Nowadays it is very relevant for researchers due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all the evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical …


Simulating Correlated Binary And Multinomial Responses Under Marginal Model Specification: The Simcormultres Package, Anestis Touloumis 2016 University of Brighton

Simulating Correlated Binary And Multinomial Responses Under Marginal Model Specification: The Simcormultres Package, Anestis Touloumis

The R Journal

We developed the R package SimCorMultRes to facilitate simulation of correlated categorical (binary and multinomial) responses under a desired marginal model specification. The simulated correlated categorical responses are obtained by applying threshold approaches to correlated continuous responses of underlying regression models and the dependence structure is parametrized in terms of the correlation matrix of the latent continuous responses. This article provides an elaborate introduction to the SimCorMultRes package demonstrating its design and usage via three examples. The package can be obtained via CRAN.


Diverse: An R Package To Analyze Diversity In Complex Systems, Miguel R. Guevara, Dominik Hartmann, Marcelo Mendoza 2016 Universidad Técnica Federico Santa María

Diverse: An R Package To Analyze Diversity In Complex Systems, Miguel R. Guevara, Dominik Hartmann, Marcelo Mendoza

The R Journal

The package diverse provides an easy-to-use interface to calculate and visualize different aspects of diversity in complex systems. In recent years, an increasing number of research projects in social and interdisciplinary sciences, including fields like innovation studies, scientometrics, economics, and network science have emphasized the role of diversification and sophistication of socioeconomic systems. However, so far no dedicated package exists that covers the needs of these emerging fields and interdisciplinary teams. Most packages about diversity tend to be created according to the demands and terminology of particular areas of natural and biological sciences. The package diverse uses interdisciplinary concepts of …


Ggfortify: Unified Interface To Visualize Statistical Results Of Popular R Packages, Yuan Yuan, Masaaki Horikoshi, Wenxuan Li 2016 Uptake Technologies, Inc.

Ggfortify: Unified Interface To Visualize Statistical Results Of Popular R Packages, Yuan Yuan, Masaaki Horikoshi, Wenxuan Li

The R Journal

The ggfortify package provides a unified interface that enables users to use one line of code to visualize statistical results of many R packages using ggplot2 idioms. With the help of ggfortify, statisticians, data scientists, and researchers can avoid the sometimes repetitive work of using the ggplot2 syntax to achieve what they need.


Comf: An R Package For Thermal Comfort Studies, Marcel Schweiker 2016 Karlsruhe Institute of Technology

Comf: An R Package For Thermal Comfort Studies, Marcel Schweiker

The R Journal

The field of thermal comfort generated a number of thermal comfort indices. Their code implementation needs to be done by individual researchers. This paper presents the R package, comf, which includes functions for common and new thermal comfort indices. Additional functions allow comparisons between the predictive performance of these indices. This paper reviews existing thermal comfort indices and available code implementations. This is followed by the description of the R package and an example how to use the R package for the comparison of different thermal comfort indices on data from a thermal comfort study.


Dcovts: Distance Covariance/Correlation For Time Series, Maria Pitsillou, Konstantinos Fokianos 2016 University of Cyprus

Dcovts: Distance Covariance/Correlation For Time Series, Maria Pitsillou, Konstantinos Fokianos

The R Journal

The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.


Ake: An R Package For Discrete And Continuous Associated Kernel Estimations, Wanbitching E. Wansouwé, Sobom M. Somé, Célestin C. Kokonendji 2016 The University of Maroua

Ake: An R Package For Discrete And Continuous Associated Kernel Estimations, Wanbitching E. Wansouwé, Sobom M. Somé, Célestin C. Kokonendji

The R Journal

Kernel estimation is an important technique in exploratory data analysis. Its utility relies on its ease of interpretation, especially based on graphical means. The Ake package is introduced for univariate density or probability mass function estimation and also for continuous and discrete regression functions using associated kernel estimators. These associated kernels have been proposed due to their specific features of variables of interest. The package focuses on associated kernel methods appropriate for continuous (bounded, positive) or discrete (count, categorical) data often found in applied settings. Furthermore, optimal bandwidths are selected by cross-validation for any associated kernel and by Bayesian methods …


Mctest: An R Package For Detection Of Collinearity Among Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf 2016 Bahauddin Zakariya University

Mctest: An R Package For Detection Of Collinearity Among Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf

The R Journal

It is common for linear regression models to be plagued with the problem of multicollinearity when two or more regressors are highly correlated. This problem results in unstable estimates of regression coefficients and causes some serious problems in validation and interpretation of the model. Different diagnostic measures are used to detect multicollinearity among regressors. Many statistical software and R packages provide few diagnostic measures for the judgment of multicollinearity. Most widely used diagnostic measures in these software are: coefficient of determination (R2), variance inflation factor/tolerance limit (VIF/TOL), eigenvalues, condition number (CN) and condition index (CI) etc. In this manuscript, we …


Condsurv: An R Package For The Estimation Of The Conditional Survival Function For Ordered Multivariate Failure Time Data, Luis Meira-Machado, Meira-Machado Sestelo 2016 University of Minho

Condsurv: An R Package For The Estimation Of The Conditional Survival Function For Ordered Multivariate Failure Time Data, Luis Meira-Machado, Meira-Machado Sestelo

The R Journal

One major goal in clinical applications of time-to-event data is the estimation of survival with censored data. The usual nonparametric estimator of the survival function is the time-honored Kaplan-Meier product-limit estimator. Though this estimator has been implemented in several R packages, the development of the condSURV R package has been motivated by recent contributions that allow the estimation of the survival function for ordered multivariate failure time data. The condSURV package provides three different approaches all based on the Kaplan-Meier estimator. In one of these approaches these quantities are estimated conditionally on current or past covariate measures. Illustration of the …


Distance Measures For Time Series In R: The Tsdist Package, Usue Mori, Alexander Mendiburu, Jose A. Lozano 2016 University of the Basque Country

Distance Measures For Time Series In R: The Tsdist Package, Usue Mori, Alexander Mendiburu, Jose A. Lozano

The R Journal

The definition of a distance measure between time series is crucial for many time series data mining tasks, such as clustering and classification. For this reason, a vast portfolio of time series distance measures has been published in the past few years. In this paper, the TSdist package is presented, a complete tool which provides a unified framework to calculate the largest variety of time series dissimilarity measures available in R at the moment, to the best of our knowledge. The package implements some popular distance measures which were not previously available in R, and moreover, it also provides wrappers …


Weighted Distance Based Discriminant Analysis: The R Package Wedibadis, Itziar Irigoien, Francesc Mestres, Concepcion Arenas 2016 University of the Basque Country UPV/EHU

Weighted Distance Based Discriminant Analysis: The R Package Wedibadis, Itziar Irigoien, Francesc Mestres, Concepcion Arenas

The R Journal

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances between a relatively small number of instances or units of known unbalanced-class membership measured on many (possibly thousands) features of any type. This is a current situation when analyzing genetic biomedical data. This discriminant rule can then be used both, as …


Computing Pareto Frontiers And Database Preferences With The Rpref Package, Patrick Roocks 2016 University of Augsburg

Computing Pareto Frontiers And Database Preferences With The Rpref Package, Patrick Roocks

The R Journal

The concept of Pareto frontiers is well-known in economics. Within the database community there exist many different solutions for the specification and calculation of Pareto frontiers, also called Skyline queries in the database context. Slight generalizations like the combination of the Pareto operator with the lexicographical order have been established under the term database preferences. In this paper we present the rPref package which allows to efficiently deal with these concepts within R. With its help, database preferences can be specified in a very similar way as in a state-of-the-art database management system. Our package provides algorithms for an …


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