Robustness In Network (Robin): An R Package For Comparison And Validation Of Communities,
2021
Universitá degli Studi della Campania
Robustness In Network (Robin): An R Package For Comparison And Validation Of Communities, Valeria Policastro, Dario Righelli, Annamaria Carissimo, Luisa Cutillo, Italia De Feis
The R Journal
In network analysis, many community detection algorithms have been developed. However, their implementation leaves unaddressed the question of the statistical validation of the results. Here, we present robin (ROBustness In Network), an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. The procedure initially detects if the community structure found by a set of algorithms is statistically significant and then compares two selected detection algorithms on the same graph to choose the one that better fits the network of interest. We demonstrate the use …
Indexnumber: An R Package For Measuring The Evolution Of Magnitudes,
2021
Universidade de Santiago de Compostela
Indexnumber: An R Package For Measuring The Evolution Of Magnitudes, Alejandro Saavedra-Nieves, Paula Saavedra-Nieves
The R Journal
Index numbers are descriptive statistical measures useful in economic settings for comparing simple and complex magnitudes registered, usually in two time periods. Although this theory has a large history, it still plays an important role in modern today’s societies where big amounts of economic data are available and need to be analyzed. After a detailed revision on classical index numbers in literature, this paper is focused on the description of the R package IndexNumber with strong capabilities for calculating them. Two of the four real data sets contained in this library are used for illustrating the determination of the index …
Pdynmc: A Package For Estimating Linear Dynamic Panel Data Models Based On Nonlinear Moment Conditions,
2021
University of Passau
Pdynmc: A Package For Estimating Linear Dynamic Panel Data Models Based On Nonlinear Moment Conditions, Markus Fritsch, Andrew Adrian Yu Pua, Joachim Schnurbus
The R Journal
This paper introduces pdynmc, an R package that provides users sufficient flexibility and precise control over the estimation and inference in linear dynamic panel data models. The package primarily allows for the inclusion of nonlinear moment conditions and the use of iterated GMM; additionally, visualizations for data structure and estimation results are provided. The current implementation reflects recent developments in literature, uses sensible argument defaults, and aligns commercial and noncommercial estimation commands. Since the understanding of the model assumptions is vital for setting up plausible estimation routines, we provide a broad introduction of linear dynamic panel data models directed towards …
The Bdpar Package: Big Data Pipelining Architecture For R,
2021
University of Vigo
The Bdpar Package: Big Data Pipelining Architecture For R, Miguel Ferreiro-Díaz, Tomás R. Cotos-Yáñez, José R. Méndez, David Ruano-Ordás
The R Journal
In the last years, big data has become a useful paradigm for taking advantage of multiple sources to find relevant knowledge in real domains (such as the design of personalized marketing campaigns or helping to palliate the effects of several fatal diseases). Big data programming tools and methods have evolved over time from a MapReduce to a pipeline-based archetype. Concretely the use of pipelining schemes has become the most reliable way of processing and analyzing large amounts of data. To this end, this work introduces bdpar, a new highly customizable pipeline-based framework (using the OOP paradigm provided by R6 …
Linear Regression With Stationary Errors: The R Package Slm,
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 …
Npcure: An R Package For Nonparametric Inference In Mixture Cure Models,
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,
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 …
Changes On Cran,
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,
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,
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,
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,
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 …
Package Wsbackfit For Smooth Backfitting Estimation Of Generalized Structured Models,
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 …
Rlumcarlo: Simulating Cold Light Using Monte Carlo Methods,
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,
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,
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,
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,
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,
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 …
R Medicine 2020: The Power Of Going Virtual,
2021
Mayo Clinic
R Medicine 2020: The Power Of Going Virtual, Elizabeth J. Atkinson, Peter D. Higgins, Denise Esserman, Michael J. Kane, Steven J. Schwager, Joseph B. Rickert, Daniella Mark, Mara Alexeev, Stephan Kadauke
The R Journal
The third annual R/Medicine conference was planned as a physical event to be held in Philadelphia at the end of August 2020. However, a nationwide lockdown induced by the COVID-19 pandemic required a swift transition to a virtual conference. This article describes the challenges and benefits we encountered with this transition and provides an overview of the conference content.
