OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Statistical Software is 24. 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 2022-01-01 to 2026-01-01.)

Article	Citations
Learning Base R (2nd Edition)	417
Fast Penalized Regression and Cross Validation for Tall Data with the oem Package	317
Exploring Data Subsets with vtree	196
fairadapt: Causal Reasoning for Fair Data Preprocessing	139
Emulation and History Matching Using the hmer Package	99
The poolr Package for Combining Independent and Dependent p Values	88
openTSNE : A Modular Python Library for t-SNE Dimensionality Reduction and Embedding	88
Spbsampling: An R Package for Spatially Balanced Sampling	78
carat: An R Package for Covariate-Adaptive Randomization in Clinical Trials	71
GET: Global Envelopes in R	69
ParMA: Parallelized Bayesian Model Averaging for Generalized Linear Models	68
Birth-and-Death Processes in Python: The BirDePy Package	60
pymle: A Python Package for Maximum Likelihood Estimation and Simulation of Stochastic Differential Equations	55
intRinsic: An R Package for Model-Based Estimation of the Intrinsic Dimension of a Dataset	55
spsur: An R Package for Dealing with Spatial Seemingly Unrelated Regression Models	46
DoubleML: An Object-Oriented Implementation of Double Machine Learning in R	44
mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R	43
stopp: An R Package for Spatio-Temporal Point Pattern Analysis	39
varTestnlme: An R Package for Variance Components Testing in Linear and Nonlinear Mixed-Effects Models	36
tlrmvnmvt: Computing High-Dimensional Multivariate Normal and Student- t Probabilities with Low-Ra	31
More on Multidimensional Scaling and Unfolding in R: smacof Version 2	30
sparsegl: An R Package for Estimating Sparse Group Lasso	29
missSBM: An R Package for Handling Missing Values in the Stochastic Block Model	29
Expanding Tidy Data Principles to Facilitate Missing Data Exploration, Visualization and Assessment of Imputations	29