pure-Python HistFactory implementation with tensors and autodiff
-
Updated
Jul 15, 2024 - Python
pure-Python HistFactory implementation with tensors and autodiff
MCMC sample analysis, kernel densities, plotting, and GUI
Ambrosia is a Python library for A/B tests design, split and result measurement
Statistical inference on machine learning or general non-parametric models
Statistics tools and utilities.
Hypothesis and statistical testing in Python
A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"
[TNNLS 2022] Significance tests of feature relevance for a black-box learner
Perform inference on algorithm-agnostic variable importance in Python
Code and data for the CIKM2021 paper "Learning Ideological Embeddings From Information Cascades"
A Bayesian model of series convergence using Gaussian sums
My Personal Machine Learning and Data Science Training Repository
Package provides python implementation of statistical inference engine
Off-Policy Interval Estimation withConfounded Markov Decision Process
Cegpy (/segpaɪ/) is a Python package for working with Chain Event Graphs. It supports learning the graphical structure of a Chain Event Graph from data, encoding of parametric and structural priors, estimating its parameters, and performing inference.
Statistical learning and inference algorithms implemented in Python 3
Code implementing Integrator Snippets, joint work with Christophe Andrieu and Chang Zhang
A little exploration of R's power for statistical inference
Bayesian inference of stochastic cellular processes with and without memory in Python.
Add a description, image, and links to the statistical-inference topic page so that developers can more easily learn about it.
To associate your repository with the statistical-inference topic, visit your repo's landing page and select "manage topics."