independence-tests

There are 16 repositories under independence-tests topic.

  • py-why/causal-learn

    Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

    Language:Python1k1596172

  • Mamba413/Ball

    Statistical Inference and Sure Independence Screening via Ball Statistics

    Language:C25361

  • wittawatj/fsic-test

    ICML 2017. Kernel-based adaptive linear-time independence test.

    Language:Python15306

  • ArnoVel/structure-identification

    Uses several statistical tests / algorithms on marginal / conditional distributions

    Language:Jupyter Notebook7302

  • youjin1207/netdep

    R package for testing network dependence

    Language:R6001

  • GZHoffie/independence-in-streams

    This repository contains code for identifying correlation in a stream of samples. The sketching of sketches algorithm and the counter matrix algorithm are implemented and benchmarked.

    Language:Jupyter Notebook51100

  • Cbhihe/visualCity

    Multivariate analysis and statistical modeling (with dimensional reduction) of NYC urban life pathologies

    Language:R2201

  • mvidela31/TSP-IT

    An Independence Test based on Data-Driven Tree-Structured Representations.

    Language:Jupyter Notebook2201

  • doerlbh/AGTIC

    Code for our paper: "Adaptive Geo-Topological Independence Criterion".

    Language:MATLAB120

  • felix-laumann/MMD_HSIC_non-stationary

    MMD and HSIC for non-stationary random processes

    Language:Jupyter Notebook1201

  • jzavatoneveth/hhg-test

    Heller-Heller-Gorfine multivariate test of association

    Language:MATLAB1310

  • majianthu/eval

    Code for the Paper "Evaluating Independence and Conditional Independence Measures"

    Language:R1100

  • Ohm-Rajpal/FinalProject

    Stats HW chat bot that solves chi-square problems involving goodness of fit, homogeneity, or independence

    Language:Java1101

  • vaitybharati/P21.-Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers-

    Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers. Assume Null Hypothesis as Ho: Independence of categorical variables (Athlete and Smoking not related). Thus Alternate Hypothesis as Ha: Dependence of categorical variables (Athlete and Smoking is somewhat/significantly related). As (p_value = 0.00038) < (α = 0.05); Reject Null Hypothesis i.e. Dependence among categorical variables Thus Athlete and Smoking is somewhat/significantly related.

    Language:Jupyter Notebook1101

  • jeanbaptisteb/ACT

    analysis of contingency tables and their residuals, with a bootstrap correction for multiple testing

    Language:Python0101

  • kalhorghazal/HealthCare-Dataset-Statistical-Analysis

    📉HealthCare Dataset Statistical Analysis, Statistical Inference course, University of Tehran

    Language:Jupyter Notebook20