lifelines
lifelines: survival analysis in Python - Published in JOSS (2019)
Intracranial Electrode Location and Analysis in MNE-Python
Intracranial Electrode Location and Analysis in MNE-Python - Published in JOSS (2022)
imodels
imodels: a python package for fitting interpretable models - Published in JOSS (2021)
PyCM
PyCM: Multiclass confusion matrix library in Python - Published in JOSS (2018)
pyhf
pyhf: pure-Python implementation of HistFactory statistical models - Published in JOSS (2021)
Pingouin
Pingouin: statistics in Python - Published in JOSS (2018)
PreliZ
PreliZ: A tool-box for prior elicitation - Published in JOSS (2023)
TextDescriptives
TextDescriptives: A Python package for calculating a large variety of metrics from text - Published in JOSS (2023)
PyAutoFit
PyAutoFit: A Classy Probabilistic Programming Language for Model Composition and Fitting - Published in JOSS (2021)
scikit-posthocs
scikit-posthocs: Pairwise multiple comparison tests in Python - Published in JOSS (2019)
effectsize
effectsize: Estimation of Effect Size Indices and Standardized Parameters - Published in JOSS (2020)
performance
performance: An R Package for Assessment, Comparison and Testing of Statistical Models - Published in JOSS (2021)
volesti
volesti: A C++ library for sampling and volume computation on convex bodies - Published in JOSS (2025)
see
see: An R Package for Visualizing Statistical Models - Published in JOSS (2021)
OnlineStats.jl
OnlineStats.jl: A Julia package for statistics on data streams - Published in JOSS (2020)
Frites
Frites: A Python package for functional connectivity analysis and group-level statistics of neurophysiological data - Published in JOSS (2022)
piecewise-regression (aka segmented regression) in Python
piecewise-regression (aka segmented regression) in Python - Published in JOSS (2021)
BioPsyKit
BioPsyKit: A Python package for the analysis of biopsychological data - Published in JOSS (2021)
VeridicalFlow
VeridicalFlow: a Python package for building trustworthy data science pipelines with PCS - Published in JOSS (2022)
HiddenMarkovModels.jl
HiddenMarkovModels.jl: generic, fast and reliable state space modeling - Published in JOSS (2024)
bayes-toolbox
bayes-toolbox: A Python package for Bayesian statistics - Published in JOSS (2023)
Reducing the efforts to create reproducible analysis code with FieldTrip
Reducing the efforts to create reproducible analysis code with FieldTrip - Published in JOSS (2024)
kalepy
kalepy: a Python package for kernel density estimation, sampling and plotting - Published in JOSS (2021)
The psycho Package
The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science - Published in JOSS (2018)
rsimsum
rsimsum: Summarise results from Monte Carlo simulation studies - Published in JOSS (2018)
Contextualized
Contextualized: Heterogeneous Modeling Toolbox - Published in JOSS (2024)
piar
piar: Price Index Aggregation in R - Published in JOSS (2024)
rempsyc
rempsyc: Convenience functions for psychology - Published in JOSS (2023)
PyUnfold
PyUnfold: A Python package for iterative unfolding - Published in JOSS (2018)
lfda
lfda: Local Fisher Discriminant Analysis in R - Published in JOSS (2019)
dml
dml: Distance Metric Learning in R - Published in JOSS (2018)
lavaanExtra
lavaanExtra: Convenience Functions for Package lavaan - Published in JOSS (2023)
popsynth
popsynth: A generic astrophysical population synthesis framework - Published in JOSS (2021)
autoplotly
autoplotly: An R package for automatic generation of interactive visualizations for statistical results - Published in JOSS (2018)
txshift
txshift: Efficient estimation of the causal effects of stochastic interventions in R - Published in JOSS (2020)
hoggorm
hoggorm: a python library for explorative multivariate statistics - Published in JOSS (2019)
Hypothesize
Hypothesize: Robust Statistics for Python - Published in JOSS (2020)
The jagstargets R package
The jagstargets R package: a reproducible workflow framework for Bayesian data analysis with JAGS - Published in JOSS (2021)
A Short Introduction to PF
A Short Introduction to PF: A C++ Library for Particle Filtering - Published in JOSS (2020)
Statmanager-kr
Statmanager-kr: A User-friendly Statistical Package for Python in Pandas - Published in JOSS (2024)
pyMultiFit: A Python library for fitting data with multiple models
pyMultiFit: A Python library for fitting data with multiple models - Published in JOSS (2025)
Synthia
Synthia: multidimensional synthetic data generation in Python - Published in JOSS (2021)
MarSwitching.jl
MarSwitching.jl: A Julia package for Markov switching dynamic models - Published in JOSS (2024)
tacmagic
tacmagic: Positron emission tomography analysis in R - Published in JOSS (2019)
PRDA
PRDA: An R package for Prospective and Retrospective Design Analysis - Published in JOSS (2021)
flusight
flusight: interactive visualizations for infectious disease forecasts - Published in JOSS (2017)
lintsampler
lintsampler: Easy random sampling via linear interpolation - Published in JOSS (2024)
wbacon
wbacon: Weighted BACON algorithms for multivariate outlier nomination (detection) and robust linear regression - Published in JOSS (2021)
Distributions
A Julia package for probability distributions and associated functions.
latentcor
latentcor: An R Package for estimating latent correlations from mixed data types - Published in JOSS (2021)
pfla
pfla: A Python Package for Dental Facial Analysis using Computer Vision and Statistical Shape Analysis - Published in JOSS (2018)
SuperNOVA
SuperNOVA: Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions in R - Published in JOSS (2023)
CVtreeMLE
CVtreeMLE: Efficient Estimation of Mixed Exposures using Data Adaptive Decision Trees and Cross-Validated Targeted Maximum Likelihood Estimation in R - Published in JOSS (2023)
plotastic
plotastic: Bridging Plotting and Statistics in Python - Published in JOSS (2024)
The stantargets R package
The stantargets R package: a workflow framework for efficient reproducible Stan-powered Bayesian data analysis pipelines - Published in JOSS (2021)
StatAid
StatAid: An R package with a graphical user interface for data analysis - Published in JOSS (2020)
biotmle
biotmle: Targeted Learning for Biomarker Discovery - Published in JOSS (2017)
gmm_diag and gmm_full
gmm_diag and gmm_full: C++ classes for multi-threaded Gaussian mixture models and Expectation-Maximisation - Published in JOSS (2017)
geostatspy
GeostatsPy Python package for spatial data analytics and geostatistics. Started as a reimplementation of GSLIB, Geostatistical Library (Deutsch and Journel, 1992) from Fortran to Python, Geostatistics in a Python package. Now with many additional methods. I hope this resources is helpful, Prof. Michael Pyrcz
miet
miet: an R package for region of interest analysis from magnetic reasonance images - Published in JOSS (2020)
statsmodels
Statsmodels: statistical modeling and econometrics in Python
lumin
LUMIN - a deep learning and data science ecosystem for high-energy physics.
gstools
GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more
collapse
Advanced and Fast Data Transformation in R
frouros
Frouros: an open-source Python library for drift detection in machine learning systems.
pyriemann
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
GeoStats.jl -- High-performance geostatistics in Julia
GeoStats.jl -- High-performance geostatistics in Julia - Published in JOSS (2018)
arkhe
Tools for cleaning rectangular data - :exclamation: This is a read-only mirror from https://codeberg.org/tesselle/arkhe
@stdlib/random-base-mt19937
A 32-bit Mersenne Twister pseudorandom number generator.
asreview-insights
Tools such as plots and metrics to analyze (simulated) reviews for ASReview LAB
StructuralEquationModels
A fast and flexible Structural Equation Modelling Framework
brglm2
Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction
@stdlib/stats-incr-kurtosis
Compute a corrected sample excess kurtosis incrementally.
@stdlib/stats-incr-maape
Compute the mean arctangent absolute percentage error (MAAPE) incrementally.