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This repository contains the code for estimating the shape parameters of the Beta distribution using a Bayesian approach. It includes implementations of Bayesian techniques, such as empirical and subjective methods.
A tool-box for prior elicitation.
Updated
Sep 13, 2024
Python
Duality of view between named variables and flat vectors in Julia
Updated
Sep 11, 2024
Julia
priorsense: an R package for prior diagnostics and sensitivity
Maximum entropy and minimum divergence models in Python
Updated
Apr 20, 2024
Jupyter Notebook
Some remarks on prior modelling for the basic reproductive number in the Susceptible-Infected-Recovered (SIR) epidemic model
Updated
Sep 18, 2023
Jupyter Notebook
A Julia package to support conjugate prior distributions.
Updated
Feb 14, 2023
Julia
This is a toy problem to show why our choices of Bayesian prior distributions and sample size are important in our knowledge of model response surface
Bayesian Inference on the risk factors for cervical cancer
Tools for the Bayesian Discount Prior Function
Regularized Levenberg-Marquardt algorithm for nonlinear regression on small size datasets
Updated
Jun 23, 2020
Python
Course Final Project of COMS4995 Deep Learning Course
Updated
May 5, 2020
Jupyter Notebook
A test of how informative priors can be
Shiny WebApp for hetprior project
Material and ms for the paper @
R package for the simulation of the prior distribution of bayesian trees by Chipman et al. (1998).
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