cliburn / sta-663-2020
☆45Updated 5 years ago
Alternatives and similar repositories for sta-663-2020:
Users that are interested in sta-663-2020 are comparing it to the libraries listed below
- Computational Statistics and Statistical Computing☆37Updated 4 years ago
- Course material for Bayesian and Modern Statistics, STA601, Duke University, Spring 2015.☆20Updated 9 years ago
- Course notes for Computational Statistics and Statistical Compuing☆63Updated 6 years ago
- Source repository for the online book Exploratory Analysis of Bayesian Models.☆22Updated this week
- ☆72Updated 6 years ago
- My solutions to the assignments in the book: "A Student’s Guide to Bayesian Statistics" by Ben Lambert.☆68Updated 10 months ago
- Educational resources☆104Updated 3 years ago
- Python code for Computer Age Statistical Inference☆52Updated 6 years ago
- Presented at Scipy Conference 2019☆126Updated 5 years ago
- Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.☆91Updated 8 months ago
- Bayesian Learning course at Stockholm University☆151Updated 10 months ago
- ☆38Updated 4 years ago
- ☆73Updated 6 years ago
- Hidden Markov models in PyMC3☆99Updated last year
- Inference case studies in jupyter☆94Updated 6 years ago
- Notebooks for https://python-programming.quantecon.org☆56Updated last month
- Statistical Rethinking: A Bayesian Course Using Python and NumPyro☆90Updated 4 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆73Updated 6 years ago
- Statistics and Machine Learning in Python☆69Updated 4 years ago
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆51Updated 8 months ago
- ☆90Updated 4 years ago
- State Space Estimation of Time Series Models in Python: Statsmodels☆44Updated 8 years ago
- Notebooks of Python and R code which illustrates basic causal inference using simulated data☆23Updated 6 years ago
- Workshop on Bayesian inference using PyMC☆27Updated 3 years ago
- Introductory overview of Bayesian inference☆44Updated 6 years ago
- Bayesian Analysis with Python - Second Edition, published by Packt☆133Updated 4 years ago
- PyData London 2019 Tutorial on Markov chain Monte Carlo with PyMC3☆156Updated 5 years ago
- Simulation based calibration and generation of synthetic data.☆50Updated last month
- Probabilistic Programming and Bayesian Computing with PyMC☆23Updated 10 months ago
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Updated 6 years ago