Editorial

Abstract

The ‘Editorial’ article from the 2019-2 issue.

On behalf of the editorial board, I am pleased to present Volume 12, Issue 1 of the R Journal and my second issue as the Editor in Chief. Since the last issue Simon Urbanek has joined the editorial board and we have made a few structural changes. First, the R Foundation has approved the R Journal having Associate Editors. This change will allow us to address the increase in submission volume. The addition of the new AE positions should help alleviate some of the workload the editors have been dealing with and will result in shorter turn-around times for submissions. Second, complete issues of the R Journal will no longer be published in a single pdf. The build process for the document was complex and time consuming and we were not seeing the volume of download that would justify the effort. Individual articles are still available and the issue layout is still shown in the “Current Issue” section of the web page.

In this issue

News from the R Foundation is included in this issue along with an update from the The R Foundation’s histoRicalg project, which documents historic and historical numerical algorithms and provides reference implementations in R. In addition, a reprint documenting the history of R, which was initially published in the History of Programming Languages. Finally, this issue features 25 contributed research articles that have been categorized below.

Papers focusing on performance and novel, domain-specific applications:

• “Comparing namedCapture with other R packages for regular expressions
• “cvcrand: a Package for Covariate-constrained Randomization and the Clustered Permutation Test for Cluster Randomization Trials
• “Indoor Positioning and Fingerprinting: The R package ipft

Data preprocessing, imputation, validation, and exploration:

• “jomo: a Flexible Package for Two-level Joint Modelling Multiple Imputation”
• “auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics”
• “Fitting tails by the empirical residual coefficient of variation: The ercv package”
• “The Landscape of R Packages for Automated Exploratory Data Analysis”
• “The R Package trafo for Transforming Linear Regression Models”
• “orthoDr: semiparametric dimension reduction via orthogonality constrained optimization”

Spatial statistics:

• “spGARCH: An R Package for Spatial and Spatiotemporal ARCH models”
• “The IDSpatialStats R package: Quantifying spatial dependence of infectious disease spread”
• “Using Web Services to Work with Geodata in R”

Time-series analysis and finance:

• “lpirfs: An R-package to estimate impulse response functions by local projections”
• “Time Series Forecasting with KNN in R: the tsfknn Package”
• “rollmatch: An R Package for Rolling Entry Matching”
• “BondValuation: An R Package for Fixed Coupon Bond Analysis”
• “Modeling regimes with extremes: the bayesdfa package for identifying and forecasting common trends and anomalies in multivariate time-series data”

Clustering:

• “roahd Package: Robust Analysis of High Dimensional Data”
• “PPCI: an R Package for Cluster Identification using Projection Pursuit”
• “ConvergenceClubs: A Package for Performing the Phillips and Sul’s Club Convergence Clustering Procedure”
• “biclustermd: An R Package for Biclustering with Missing Values”

And supervised modeling:

• “dr4pl: A stable convergence algorithm for the 4 Parameter Logistic model”
• “coxed: An R Package for Computing Duration Based Quantities from the Cox Proportional Hazards Model”
• “Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM”
• “Associative Classification in R: arc, arulesCBA, and rCBA”
• “HCmodelSets: An R Package for Specifying Sets of Well-fitting Models in High Dimensions”