Statistical Modeling
Showing 10 of 10 projects
An automatic forecasting procedure for time series data with multiple seasonality and linear or non-linear growth.
An open-source forecasting tool for time series data with multiple seasonality and linear or non-linear growth.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal probabilistic modeling.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal representation of computable probability distributions.
A Python toolkit for causal and probabilistic reasoning using graphical models like Bayesian Networks and Structural Equation Models.
A lightweight probabilistic programming library using NumPy and JAX for autograd and JIT compilation to GPU/TPU/CPU.
A Python tutorial and cookbook for implementing Bayesian modeling techniques using PyMC3.
An open-source Python library for probabilistic time series modeling with both frequentist and Bayesian inference methods.
An R package for estimating causal effects in time series using Bayesian structural time-series models.
Python code and examples for Bayesian statistics from the book 'Think Bayes: Bayesian Statistics Made Simple'.
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