stan
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A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
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Apr 28, 2022 - Python
Hi,
is there any plan to implement the Generalized Pareto Distribution in brms (paul-buerkner/brms#110 (comment))? I am playing around with an extreme values analysis and it looks like extremes collected as Peak Over Threshold are better represented by the GPD instead of the generalized extreme value distribution, which I am so happy to see already in `b
PyStan, the Python interface to Stan
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Feb 17, 2021 - Python
Bayesian Data Analysis demos for Python
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Dec 16, 2021 - Jupyter Notebook
RStan, the R interface to Stan
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May 6, 2022 - C++
Bayesian analysis + tidy data + geoms (R package)
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Feb 22, 2022 - R
clean up Doxygen
Description
Describe the issue as clearly as possible. Issues are meant for bug reports and feature requests. The issue should contain enough information for a developer to put together a solution.
If this is a general question, please post to the forums.
Example
Here's the current errors.
mkdir -p doc/api
doxygen doxygen/doxygen.cfg
warn
Bayesian Data Analysis demos for R
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Mar 25, 2022 - R
bayesplot R package for plotting Bayesian models
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Mar 31, 2022 - R
rstanarm R package for Bayesian applied regression modeling
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Apr 29, 2022 - R
shinystan R package and ShinyStan GUI
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Mar 3, 2022 - R
NATS Streaming Operator
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May 26, 2021 - Go
Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
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Feb 23, 2021 - Jupyter Notebook
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.
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Nov 25, 2020 - R
Tutorial on model assessment, model selection and inference after model selection
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Mar 2, 2022 - HTML
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
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Mar 24, 2022 - R
Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
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Dec 3, 2021 - Julia
Teaching materials for BayesCog at Faculty of Psychology, University of Vienna
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Jun 17, 2021 - R
Projection predictive variable selection
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May 7, 2022 - R
Bayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.
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Dec 2, 2018 - HTML
Vignettes
Vignettes to-do list:
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filtering returned parameters from
$draws()
Showcase how one can read in only selected parameters. -
variational inference (done in #210)
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optimization (done in #210)
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profiling (done in #435)
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standalone generate_quantities
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vignette on how to use different draws formats
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example with changing adapt delta and max_tr
Matlab interface to Stan, a package for Bayesian inference
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Dec 23, 2021 - MATLAB
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Description:
We need some easy to follow instructions on how to use the core Stan inside a user-written C++ program. See stan-dev/stan#3085 for example.
The instruction can simply guide through the task of compiling one of the models and running MCMC with the services. The biggest challenges are typically all the dependencies that we need to include in the C++