dpsimpson

Pinned Repositories

academic-kickstart
Easily create a beautiful website using Academic and Hugo
Language:Shell00
bayesplot
bayesplot R package for plotting Bayesian models
Language:R00
blog
Language:HTML04
boundary_avoiding_priors
A fast simulation study for checking if boundary avoiding priors are a good idea for variance parameters in a hierarchical regression. They aren't.
Language:R00
CARstan
Conditional autoregressive models in Stan
Language:Stan21
dpsimpson.github.io
A website? For an academic? Groundbreaking.
Language:Ruby01
example-models
Example models for Stan
Language:HTML00
fortuna
A Library for Uncertainty Quantification.
Language:Python00
jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Language:Python00
lmm_python
Just playing
00

dpsimpson's Repositories

dpsimpson/CARstan
Conditional autoregressive models in Stan
Language:Stan21
dpsimpson/academic-kickstart
Easily create a beautiful website using Academic and Hugo
Language:Shell00
dpsimpson/bayesplot
bayesplot R package for plotting Bayesian models
Language:R00
dpsimpson/blog
Language:HTML04
dpsimpson/boundary_avoiding_priors
A fast simulation study for checking if boundary avoiding priors are a good idea for variance parameters in a hierarchical regression. They aren't.
Language:R00
dpsimpson/dpsimpson.github.io
A website? For an academic? Groundbreaking.
Language:Ruby01
dpsimpson/example-models
Example models for Stan
Language:HTML00
dpsimpson/fortuna
A Library for Uncertainty Quantification.
Language:Python00
dpsimpson/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Language:Python00
dpsimpson/lmm_python
Just playing
00
dpsimpson/math
Stan Math Library
Language:C++00
dpsimpson/numbats-website
Non-Uniform Monash Business Analytic Team Website
Language:HTML
dpsimpson/openai-cookbook
Examples and guides for using the OpenAI API
dpsimpson/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
dpsimpson/rstanarm
rstanarm R package for Bayesian applied regression modeling
Language:R
dpsimpson/stan
Stan development repository (home page is linked below). The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Language:R