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Linear Regression With Stationary Errors: The R Package Slm, Emmanuel Caron, Jérôme Dedecker, Bertrand Michel 2021 Avignon Université

Linear Regression With Stationary Errors: The R Package Slm, Emmanuel Caron, Jérôme Dedecker, Bertrand Michel

The R Journal

This paper introduces the R package slm, which stands for Stationary Linear Models. The package contains a set of statistical procedures for linear regression in the general context where the error process is strictly stationary with a short memory. We work in the setting of Hannan (1973), who proved the asymptotic normality of the (normalized) least squares estimators (LSE) under very mild conditions on the error process. We propose different ways to estimate the asymptotic covariance matrix of the LSE and then to correct the type I error rates of the usual tests on the parameters (as well as confidence …


A Method For Deriving Information From Running R Code, Mark P. J. van der Loo 2021 Statistics Netherlands

A Method For Deriving Information From Running R Code, Mark P. J. Van Der Loo

The R Journal

It is often useful to tap information from a running R script. Obvious use cases include monitoring the consumption of resources (time, memory) and logging. Perhaps less obvious cases include tracking changes in R objects or collecting the output of unit tests. In this paper, we demonstrate an approach that abstracts the collection and processing of such secondary information from the running R script. Our approach is based on a combination of three elements. The first element is to build a customized way to evaluate code. The second is labeled local masking and it involves temporarily masking a user-facing function …


Npcure: An R Package For Nonparametric Inference In Mixture Cure Models, Ana López-Cheda, M Amalia Jácome, Ignacio López-de-Ullibarri 2021 University of Nebraska - Lincoln

Npcure: An R Package For Nonparametric Inference In Mixture Cure Models, Ana López-Cheda, M Amalia Jácome, Ignacio López-De-Ullibarri

The R Journal

Mixture cure models have been widely used to analyze survival data with a cure fraction. They assume that a subgroup of the individuals under study will never experience the event (cured subjects). So, the goal is twofold: to study both the cure probability and the failure time of the uncured individuals through a proper survival function (latency). The R package npcure implements a completely nonparametric approach for estimating these functions in mixture cure models, considering right-censored survival times. Nonparametric estimators for the cure probability and the latency as functions of a covariate are provided. Bootstrap bandwidth selectors for the estimators …


Seedcca: An Integrated R-Package For Canonical Correlation Analysis And Partial Least Squares, Bo-Young Kim, Yunju Im, Jae Keun Yoo 2021 Celltrion

Seedcca: An Integrated R-Package For Canonical Correlation Analysis And Partial Least Squares, Bo-Young Kim, Yunju Im, Jae Keun Yoo

The R Journal

Canonical correlation analysis (CCA) has a long history as an explanatory statistical method in high-dimensional data analysis and has been successfully applied in many scientific fields such as chemometrics, pattern recognition, genomic sequence analysis, and so on. The so-called seedCCA is a newly developed R package that implements not only the standard and seeded CCA but also partial least squares. The package enables us to fit CCA to large-p and small-n data. The paper provides a complete guide. Also, the seeded CCA application results are compared with the regularized CCA in the existing R package. It is believed that the …


Conference Report Of Why R? Turkey 2021, Mustafa Cavus, Olgun Aydin, Ozan Evkaya, Ozancan Ozdemir, Deniz Bezer, Ugur Dar 2021 Eskisehir Technical University

Conference Report Of Why R? Turkey 2021, Mustafa Cavus, Olgun Aydin, Ozan Evkaya, Ozancan Ozdemir, Deniz Bezer, Ugur Dar

The R Journal

The Why R? Turkey 2021 as a three-day online conference was organized to bring together researchers and professionals from Turkey on April 16-17-18, 2021. We hereby aimed to promote the R community in Turkey by bringing R users with different backgrounds such as genetics, sociology, finance, economy, bio-statistics. There were 8 thematic sessions and 18 invited speakers. In this article, it is aimed to describe the preparation phase, technical details, and the impact of the conference on audience.


News From The Forwards Taskforce, Heather Turner 2021 University of Warwick

News From The Forwards Taskforce, Heather Turner

The R Journal

Forwards is an R Foundation taskforce working to widen the participation of underrepresented groups in the R project and in related activities, such as the useR! conference. This report rounds up activities of the taskforce during the first half of 2021.


Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis 2021 WU Wirtschaftsuniversität Wien

Changes On Cran, Kurt Hornik, Uwe Ligges, Achim Zeileis

The R Journal

In the past 6 months, 1290 new packages were added to the CRAN package repository. 116 packages were unarchived and 467 were archived. The following shows the growth of the number of active packages in the CRAN package repository


Regularized Transformation Models: The Tramnet Package, Lucas Kook, Torsten Hothorn 2021 Universität Zürich

Regularized Transformation Models: The Tramnet Package, Lucas Kook, Torsten Hothorn

The R Journal

The tramnet package implements regularized linear transformation models by combining the flexible class of transformation models from tram with constrained convex optimization implemented in CVXR. Regularized transformation models unify many existing and novel regularized regression models under one theoretical and computational framework. Regularization strategies implemented for transformation models in tramnet include the Lasso, ridge regression, and the elastic net and follow the parameterization in glmnet. Several functionalities for optimizing the hyperparameters, including model-based optimization based on the mlrMBO package, are implemented. A multitude of S3 methods is deployed for visualization, handling, and simulation purposes. This work aims at illustrating all …


The Hbv.Ianigla Hydrological Model, Ezequiel Toum, Mariano H. Masiokas, Ricardo Villalba, Pierre Pitte, Lucas Ruiz 2021 IANIGLA-CONICET

The Hbv.Ianigla Hydrological Model, Ezequiel Toum, Mariano H. Masiokas, Ricardo Villalba, Pierre Pitte, Lucas Ruiz

The R Journal

Over the past 40 years, the HBV (Hydrologiska Byråns Vattenbalansavdelning) hydrological model has been one of the most used worldwide due to its robustness, simplicity, and reliable results. Despite these advantages, the available versions impose some limitations for research studies in mountain watersheds dominated by ice-snow melt runoff (i.e., no glacier module, a limited number of elevation bands, among other constraints). Here we present HBV.IANIGLA, a tool for hydroclimatic studies in regions with steep topography and/or cryospheric processes which provides a modular and extended implementation of the HBV model as an R package. To our knowledge, this is the first …


Clustcurv: An R Package For Determining Groups In Multiple Curves, Nora M. Villanueva, Marta Sestelo, Luis Meira-Machado, Javier Roca-Pardiñas 2021 University of Vigo

Clustcurv: An R Package For Determining Groups In Multiple Curves, Nora M. Villanueva, Marta Sestelo, Luis Meira-Machado, Javier Roca-Pardiñas

The R Journal

In many situations, it could be interesting to ascertain whether groups of curves can be performed, especially when confronted with a considerable number of curves. This paper introduces an R package, known as clustcurv, for determining clusters of curves with an automatic selection of their number. The package can be used for determining groups in multiple survival curves as well as for multiple regression curves. Moreover, it can be used with large numbers of curves. An illustration of the use of clustcurv is provided, using both real data examples and artificial data


Towards A Grammar For Processing Clinical Trial Data, Michael J. Kane 2021 Yale University

Towards A Grammar For Processing Clinical Trial Data, Michael J. Kane

The R Journal

The goal of this paper is to help define a path toward a grammar for processing clinical trials by a) defining a format in which we would like to represent data from standardized clinical trial data b) describing a standard set of operations to transform clinical trial data into this format, and c) to identify a set of verbs and other functionality to facilitate data processing and encourage reproducibility in the processing of these data. It provides a background on standard clinical trial data and goes through a simple preprocessing example illustrating the value of the proposed approach through the …


R Foundation News, Torsten Hothorn 2021 Universität Zürich

R Foundation News, Torsten Hothorn

The R Journal

Membership fees and donations received between 2021-01-29 and 2021-07-05.


Package Wsbackfit For Smooth Backfitting Estimation Of Generalized Structured Models, Javier Roca-Pardiñas, María Xosé Rodríguez-Álvarez, Stefan Sperlich 2021 University of Vigo

Package Wsbackfit For Smooth Backfitting Estimation Of Generalized Structured Models, Javier Roca-Pardiñas, María Xosé Rodríguez-Álvarez, Stefan Sperlich

The R Journal

A package is introduced that provides the weighted smooth backfitting estimator for a large family of popular semiparametric regression models. This family is known as generalized structured models, comprising, for example, generalized varying coefficient model, generalized additive models, mixtures, potentially including parametric parts. The kernel-based weighted smooth backfitting belongs to the statistically most efficient procedures for this model class. Its asymptotic properties are well-understood thanks to the large body of literature about this estimator. The introduced weights allow for the inclusion of sampling weights, trimming, and efficient estimation under heteroscedasticity. Further options facilitate easy handling of aggregated data, prediction, and …


Dchaos: An R Package For Chaotic Time Series Analysis, Julio E. Sandubete, Lorenzo Escot 2021 Complutense University of Madrid

Dchaos: An R Package For Chaotic Time Series Analysis, Julio E. Sandubete, Lorenzo Escot

The R Journal

Chaos theory has been hailed as a revolution of thoughts and attracting ever-increasing attention of many scientists from diverse disciplines. Chaotic systems are non-linear deterministic dynamic systems which can behave like an erratic and apparently random motion. A relevant field inside chaos theory is the detection of chaotic behavior from empirical time-series data. One of the main features of chaos is the well-known initial-value sensitivity property. Methods and techniques related to testing the hypothesis of chaos try to quantify the initial-value sensitive property estimating the so-called Lyapunov exponents. This paper describes the main estimation methods of the Lyapunov exponent from …


Rlumcarlo: Simulating Cold Light Using Monte Carlo Methods, Sebastian Kreutzer, Johannes Friedrich, Vasilis Pagonis, Christian Laag, Ena Rajovic, Christoph Schmidt 2021 Aberystwyth University

Rlumcarlo: Simulating Cold Light Using Monte Carlo Methods, Sebastian Kreutzer, Johannes Friedrich, Vasilis Pagonis, Christian Laag, Ena Rajovic, Christoph Schmidt

The R Journal

The luminescence phenomena of insulators and semiconductors (e.g., natural minerals such as quartz) have various application domains. For instance, Earth Sciences and archaeology exploit luminescence as a dating method. Herein, we present the R package RLumCarlo implementing sets of luminescence models to be simulated with Monte Carlo (MC) methods. MC methods make a powerful ally to all kinds of simulation attempts involving stochastic processes. Luminescence production is such a stochastic process in the form of charge (electron-hole pairs) interaction within insulators and semiconductors. To simulate luminescence-signal curves, we distribute single and independent MC processes to virtual MC clusters. RLumCarlo comes …


Reproducible Summary Tables With The Gtsummary Package, Daniel D. Sjoberg, Karissa Whiting, Michael Curry, Jessica A. Lavery, Joseph Larmarange 2021 Memorial Sloan Kettering Cancer Center

Reproducible Summary Tables With The Gtsummary Package, Daniel D. Sjoberg, Karissa Whiting, Michael Curry, Jessica A. Lavery, Joseph Larmarange

The R Journal

The gtsummary package provides an elegant and flexible way to create publication-ready summary tables in R. A critical part of the work of statisticians, data scientists, and analysts is summarizing data sets and regression models in R and publishing or sharing polished summary tables. The gtsummary package was created to streamline these everyday analysis tasks by allowing users to easily create reproducible summaries of data sets, regression models, survey data, and survival data with a simple interface and very little code. The package follows a tidy framework, making it easy to integrate with standard data workflows, and offers many table …


Rocnreg: An R Package For Receiver Operating Characteristic Curve Inference With And Without Covariates, María Xosé Rodríguez-Álvarez, Vanda Inácio 2021 IKERBASQUE

Rocnreg: An R Package For Receiver Operating Characteristic Curve Inference With And Without Covariates, María Xosé Rodríguez-Álvarez, Vanda Inácio

The R Journal

This paper introduces the package ROCnReg that allows estimating the pooled ROC curve, the covariate-specific ROC curve, and the covariate-adjusted ROC curve by different methods, both from (semi) parametric and nonparametric perspectives and within Bayesian and frequentist paradigms. From the estimated ROC curve (pooled, covariate-specific, or covariate-adjusted), several summary measures of discriminatory accuracy, such as the (partial) area under the ROC curve and the Youden index, can be obtained. The package also provides functions to obtain ROC-based optimal threshold values using several criteria, namely, the Youden index criterion and the criterion that sets a target value for the false positive …


News From The Bioconductor Project, Bioconductor Core Team 2021 University of Nebraska - Lincoln

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.13 was released on 20 May, 2021. It is compatible with R 4.1.0 and consists of 2042 software packages, 406 experiment data packages, 965 up-to-date annotation packages, and 29 workflows.


Statistical Quality Control With The Qcr Package, Miguel Flores, Rubén Fernández-Casal, Salvador Naya, Javier Tarrío-Saavedra 2021 MODES

Statistical Quality Control With The Qcr Package, Miguel Flores, Rubén Fernández-Casal, Salvador Naya, Javier Tarrío-Saavedra

The R Journal

The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC (qcc, MSQC), qcr provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, [], S, R, p, np, c, u, EWMA, and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T2 , MEWMA and MCUSUM. As …


Jmcmprsk: An R Package For Joint Modelling Of Longitudinal And Survival Data With Competing Risks, Hong Wang, Ning Li, Shanpeng Li, Gang Li 2021 Central South University

Jmcmprsk: An R Package For Joint Modelling Of Longitudinal And Survival Data With Competing Risks, Hong Wang, Ning Li, Shanpeng Li, Gang Li

The R Journal

In this paper, we describe an R package named JMcmprsk, for joint modelling of longitudinal and survival data with competing risks. The package in its current version implements two joint models of longitudinal and survival data proposed to handle competing risks survival data together with continuous and ordinal longitudinal outcomes respectively (Elashoff et al., 2008; Li et al., 2010). The corresponding R implementations are further illustrated with real examples. The package also provides simulation functions to simulate datasets for joint modelling with continuous or ordinal outcomes under the competing risks scenario, which provide useful tools to validate and evaluate …


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