R Journal

Papers
(The TQCC of R Journal is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-09-01 to 2025-09-01.)
ArticleCitations
pCODE: Estimating Parameters of ODE Models45
knitrdata: A Tool for Creating Standalone Rmarkdown Source Documents30
RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests26
A Software Tool For Sparse Estimation Of A General Class Of High-dimensional GLMs17
Robust Functional Linear Regression Models16
Computer Algebra in R Bridges a Gap Between Symbolic Mathematics and Data in the Teaching of Statistics and Data Science14
GenMarkov: Modeling Generalized Multivariate Markov Chains in R13
Resampling Fuzzy Numbers with Statistical Applications: FuzzyResampling Package13
tvReg: Time-varying Coefficients in Multi-Equation Regression in R10
markovMSM: An R Package for Checking the Markov Condition in Multi-State Survival Data9
htestClust: A Package for Marginal Inference of Clustered Data Under Informative Cluster Size8
UpAndDownPlots: An R Package for Displaying Absolute and Percentage Changes8
clustAnalytics: An R Package for Assessing Stability and Significance of Communities in Networks8
A Workflow for Estimating and Visualising Excess Mortality During the COVID-19 Pandemic7
The Concordance Test, an Alternative to Kruskal-Wallis Based on the Kendall-$\tau$ Distance: An R Package7
Tidy Data Neatly Resolves Mass-Spectrometry's Ragged Arrays7
combinIT: An R Package for Combining Interaction Tests for Unreplicated Two-Way Tables7
ebmstate: An R Package For Disease Progression Analysis Under Empirical Bayes Cox Models7
ppseq: An R Package for Sequential Predictive Probability Monitoring7
Identifying Counterfactual Queries with the R Package cfid6
bootCT: An R Package for Bootstrap Cointegration Tests in ARDL Models6
Will the Real Hopkins Statistic Please Stand Up?6
Updates to the R Graphics Engine: One Person's Chart Junk is Another's Chart Treasure6
Remembering Friedrich "Fritz" Leisch6
R-miss-tastic: a unified platform for missing values methods and workflows6
metapack: An R Package for Bayesian Meta-Analysis and Network Meta-Analysis with a Unified Formula Interface6
Multivariate Subgaussian Stable Distributions in R6
Log Likelihood Ratios for Common Statistical Tests Using the likelihoodR Package5
Onlineforecast: An R Package for Adaptive and Recursive Forecasting5
Statistical Models for Repeated Categorical Ratings: The R Package rater5
logitFD: an R package for functional principal component logit regression5
dbcsp: User-friendly R package for Distance-Based Common Spatial Patterns5
Rfssa: An R Package for Functional Singular Spectrum Analysis5
GPUmatrix: Seamlessly harness the power of GPU computing in R4
A Hexagon Tile Map Algorithm for Displaying Spatial Data4
pencal: an R Package for the Dynamic Prediction of Survival with Many Longitudinal Predictors4
Power and Sample Size for Longitudinal Models in R -- The longpower Package and Shiny App4
SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models3
Inference for Network Count Time Series with the R Package PNAR3
binGroup2: Statistical Tools for Infection Identification via Group Testing3
ClusROC: An R Package for ROC Analysis in Three-Class Classification Problems for Clustered Data3
APCI: An R and Stata Package for Visualizing and Analyzing Age-Period-Cohort Data3
singR: An R Package for Simultaneous Non-Gaussian Component Analysis for Data Integration3
WLinfer: Statistical Inference for Weighted Lindley Distribution3
Advancing Reproducible Research by Publishing R Markdown Notebooks as Interactive Sandboxes Using the learnr Package3
multiocc: An R Package for Spatio-Temporal Occupancy Models for Multiple Species3
wavScalogram: An R Package with Wavelet Scalogram Tools for Time Series Analysis3
RobustCalibration: Robust Calibration of Computer Models in R3
CIMTx: An R Package for Causal Inference with Multiple Treatments using Observational Data3
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