💫 Models for the spaCy Natural Language Processing (NLP) library

This is a implementation of the 3D FLAME model in PyTorch

Tensorflow framework for the FLAME 3D head model. The code demonstrates how to sample 3D heads from the model, fit the model to 2D or 3D keypoints, and how to generate textured head meshes from Images.

calibrate ETAS, simulate using ETAS, estimate completeness magnitude & magnitude frequency distribution

A library for discrete-time Markov chains analysis.

Applied Econometrics Library for Python

PyForecast is a statistical modeling tool used by Reclamation water managers and reservoir operators to train and build predictive models for seasonal inflows and streamflows. PyForecast allows users to make current water-year forecasts using models developed with the program.

Implementation of the conjugate prior table for Bayesian Statistics

Generic goodness of fit tests for random plain old data

Implementation of backward elimination algorithm used for dimensionality reduction for improving the performance of risk calculation in life insurance industry.

Keyphrase Extraction Review

A Bayesian model of series convergence using Gaussian sums

Generate synthetic time series data.

Python implementation of STATIS for analysis of several data tables

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.

Official Implementation of the paper "Fair Generalized Linear Models with a Convex Penalty."

Python package to model count data through maximum likelihood estimation.

scikit-learn wrapper for generalized linear mixed model methods in R

Implementation of Joint Fairness Model with Applications to Risk Predictions for Under-represented Populations

A statistical model of the COVID-19 vaccination campaign. It segments the population into agnostics, pro-, and anti-vaccines. Vaccination is modeled as a Poisson process, and social pressure on the population can change their views on vaccines. The model can faithfully reproduce real-world data.