Topic: stan Goto Github
Some thing interesting about stan
Some thing interesting about stan
stan,Bayesian Data Analysis demos for Matlab/Octave
User: avehtari
Home Page: http://www.stat.columbia.edu/~gelman/book/
stan,Bayesian Data Analysis demos for Python
User: avehtari
Home Page: https://avehtari.github.io/BDA_course_Aalto/demos.html#BDA_Python_demos
stan,Bayesian Data Analysis demos for R
User: avehtari
Home Page: https://avehtari.github.io/BDA_course_Aalto/demos.html
stan,Case studies on model assessment, model selection and inference after model selection
User: avehtari
Home Page: https://users.aalto.fi/~ave/casestudies.html
stan,Inference case studies in knitr
User: betanalpha
stan,Matlab interface to Stan, a package for Bayesian inference
User: brian-lau
stan,Bayesian spatial analysis
User: connordonegan
Home Page: https://connordonegan.github.io/geostan
stan,Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
Organization: epiforecasts
Home Page: https://epiforecasts.io/EpiNow2/dev/
stan,Tools to enable flexible and efficient hierarchical nowcasting of epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes.
Organization: epinowcast
Home Page: https://package.epinowcast.org/
stan,Noisy network measurement with stan
User: jg-you
stan,'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
User: jgabry
Home Page: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssa.12378
stan,worked R examples
User: julianfaraway
stan,Teaching materials for BayesCog at Faculty of Psychology, University of Vienna
User: lei-zhang
Home Page: https://github.com/lei-zhang/BayesCog_Wien
stan,Bayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.
User: luisdamiano
stan,:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
User: m-clark
Home Page: https://m-clark.github.io/bayesian-basics/
stan,Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
User: m-clark
stan,👓 Functions related to R visualizations
User: m-clark
Home Page: https://m-clark.github.io/visibly
stan,『StanとRでベイズ統計モデリング』のサポートページです.
User: matsuurakentaro
Home Page: http://www.kyoritsu-pub.co.jp/bookdetail/9784320112421
stan,library of C++ functions that support applications of Stan in Pharmacometrics
Organization: metrumresearchgroup
stan,Bayesian analysis + tidy data + geoms (R package)
User: mjskay
Home Page: http://mjskay.github.io/tidybayes
stan,NATS Streaming Operator
Organization: nats-io
stan,{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
User: nicholasjclark
Home Page: https://nicholasjclark.github.io/mvgam/
stan,brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
User: paul-buerkner
Home Page: https://paul-buerkner.github.io/brms/
stan,Materials for teaching R and tidyverse
User: perlatex
stan,Reproducible Bayesian data analysis pipelines with targets and cmdstanr
Organization: ropensci
Home Page: https://docs.ropensci.org/stantargets
stan,BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
User: roualdes
Home Page: https://roualdes.github.io/bridgestan
stan,idealstan offers item-response theory (IRT) ideal-point estimation for binary, ordinal, counts and continuous responses with time-varying and missing-data inference. Latent space model also included. Full and approximate Bayesian sampling with 'Stan' (www.mc-stan.org).
User: saudiwin
Home Page: https://cran.r-project.org/web/packages/idealstan/index.html
stan,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
Organization: sciml
Home Page: https://docs.sciml.ai/DiffEqBayes/stable/
stan,Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
User: sibylhe
stan,bayesplot R package for plotting Bayesian models
Organization: stan-dev
Home Page: https://mc-stan.org/bayesplot
stan,CmdStanR: the R interface to CmdStan
Organization: stan-dev
Home Page: https://mc-stan.org/cmdstanr/
stan,loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Organization: stan-dev
Home Page: https://mc-stan.org/loo
stan,The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Organization: stan-dev
Home Page: https://mc-stan.org
stan,Projection predictive variable selection
Organization: stan-dev
Home Page: https://mc-stan.org/projpred/
stan,PyStan, the Python interface to Stan
Organization: stan-dev
stan,RStan, the R interface to Stan
Organization: stan-dev
Home Page: https://mc-stan.org
stan,rstanarm R package for Bayesian applied regression modeling
Organization: stan-dev
Home Page: https://mc-stan.org/rstanarm
stan,Tools for Developing R Packages Interfacing with Stan
Organization: stan-dev
Home Page: https://mc-stan.org/rstantools
stan,shinystan R package and ShinyStan GUI
Organization: stan-dev
Home Page: https://mc-stan.org/shinystan
stan,Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Organization: stan-dev
Home Page: https://mc-stan.org
stan,Emacs mode for Stan.
Organization: stan-dev
stan,Materials from Stan conferences
Organization: stan-dev
Home Page: https://mc-stan.org/
stan,Stanマニュアルの日本語への翻訳プロジェクト
Organization: stan-ja
stan,This repository holds slides and code for a full Bayesian statistics graduate course.
User: storopoli
stan,A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Organization: uber
Home Page: https://orbit-ml.readthedocs.io/en/stable/
stan,:book: R 语言数据分析实战(写作中) Data Analysis in Action Using R
User: xiangyunhuang
Home Page: https://bookdown.org/xiangyun/data-analysis-in-action/
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