effectsize
effectsize: Estimation of Effect Size Indices and Standardized Parameters - Published in JOSS (2020)
Methods and Algorithms for Correlation Analysis in R
Methods and Algorithms for Correlation Analysis in R - Published in JOSS (2020)
tidynamics
tidynamics: A tiny package to compute the dynamics of stochastic and molecular simulations - Published in JOSS (2018)
statsExpressions
statsExpressions: R Package for Tidy Dataframes and Expressions with Statistical Details - Published in JOSS (2021)
dython: A Set of Analysis and Visualization Tools for Data and Variables in Python
dython: A Set of Analysis and Visualization Tools for Data and Variables in Python - Published in JOSS (2025)
The psycho Package
The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science - Published in JOSS (2018)
Correlation Trait Loci (CTL) mapping
Correlation Trait Loci (CTL) mapping: phenotype network inference subject to genotype - Published in JOSS (2016)
pyerrors
Error propagation and statistical analysis for Monte Carlo simulations in lattice QCD and statistical mechanics using autograd.
ANCOMBC
Differential abundance (DA) and correlation analyses for microbial absolute abundance data
savannacorridors
Analysis of palaeoecological records across South-East Asia to determine the evidence for regime shifts between open savannas and dense tropical forests occurred since the Last Glacial Maximum
@stdlib/stats-pcorrtest
Compute a Pearson product-moment correlation test between paired samples.
copent
R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test
@stdlib/stats-incr-mpcorrdist
Compute a moving sample Pearson product-moment correlation distance incrementally.
@stdlib/stats-incr-mapcorr
Compute a moving sample absolute Pearson product-moment correlation coefficient incrementally.
@stdlib/stats-incr-covmat
Compute an unbiased sample covariance matrix incrementally.
@stdlib/stats-incr-covariance
Compute an unbiased sample covariance incrementally.
stats-incr-pcorr
Compute a sample Pearson product-moment correlation coefficient.
@stdlib/stats-incr-pcorrdist
Compute a sample Pearson product-moment correlation distance.
@stdlib/stats-incr-apcorr
Compute a sample absolute Pearson product-moment correlation coefficient.
@stdlib/stats-incr-pcorrmat
Compute a sample Pearson product-moment correlation matrix incrementally.
@stdlib/stats-incr-pcorrdistmat
Compute a sample Pearson product-moment correlation distance matrix incrementally.
@stdlib/stats-incr-mcovariance
Compute a moving unbiased sample covariance incrementally.
@stdlib/stats-incr-mpcorr
Compute a moving sample Pearson product-moment correlation coefficient incrementally.
@stdlib/stats-incr-pcorr2
Compute a squared sample Pearson product-moment correlation coefficient.
@stdlib/stats-incr-mpcorr2
Compute a moving squared sample Pearson product-moment correlation coefficient incrementally.
https://github.com/cgohlke/icsdll
Interface to the image correlation spectroscopy library ICSx64.dll.
https://github.com/felixpatzelt/scorr
Fast and flexible two- and three-point correlation analysis for time series using spectral methods.
mcorr
Inferring bacterial recombination rates from large-scale sequencing datasets.
https://github.com/ajayarunachalam/msda
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
matrixCorr
Scalable computation of correlation matrices using optimized C++ routines
corrp
corrp: An R package for multiple correlation-like analysis and clustering in mixed data - Published in JOSS (2025)
stats-base-ndarray-dcovarmtk
Compute the covariance of two one-dimensional double-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm.
dark_matter_flow_dataset
Dark matter flow dataset from cosmological N-body simulation
stats-strided-dcovarmtk
Calculate the covariance of two double-precision floating-point strided arrays provided known means and using a one-pass textbook algorithm.
https://github.com/amazon-science/beyondcorrelation
Implementation of the paper: Beyond Correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge
stats-strided-dcovmatmtk
Compute the covariance matrix for an `M` by `N` double-precision floating-point matrix `A` and assigns the results to a matrix `B` when provided known means and using a one-pass textbook algorithm.