• 设为首页
  • 点击收藏
  • 手机版
    手机扫一扫访问
    迪恩网络手机版
  • 关注官方公众号
    微信扫一扫关注
    迪恩网络公众号

brian-lau/MatlabStan: Matlab interface to Stan, a package for Bayesian inference

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

brian-lau/MatlabStan

开源软件地址(OpenSource Url):

https://github.com/brian-lau/MatlabStan

开源编程语言(OpenSource Language):

MATLAB 100.0%

开源软件介绍(OpenSource Introduction):

MatlabStan

Stan Logo

A Matlab interface to Stan, a package for Bayesian inference.

For more information on Stan and its modeling language, see the Stan User's Guide and Reference Manual at http://mc-stan.org/.

Installation

Details can be found in the Getting started page of the wiki.

Example

The following is the classic 'eight schools' example from Section 5.5 of Gelman et al (2003). The output can be compared to that obtained using the Rstan and Pystan interfaces.

schools_code = {
   'data {'
   '    int<lower=0> J;         // number of schools '
   '    real y[J];              // estimated treatment effects'
   '    real<lower=0> sigma[J]; // s.e. of effect estimates '
   '}'
   'parameters {'
   '    real mu; '
   '    real<lower=0> tau;'
   '    real eta[J];'
   '}'
   'transformed parameters {'
   '    real theta[J];'
   '    for (j in 1:J)'
   '    theta[j] = mu + tau * eta[j];'
   '}'
   'model {'
   '    eta ~ normal(0, 1);'
   '    y ~ normal(theta, sigma);'
   '}'
};
  
schools_dat = struct('J',8,...
                     'y',[28 8 -3 7 -1 1 18 12],...
                     'sigma',[15 10 16 11 9 11 10 18]);

fit = stan('model_code',schools_code,'data',schools_dat);

print(fit);

eta = fit.extract('permuted',true).eta;
mean(eta)

A collection of Matlab-specific examples is available in the wiki.

Need help?

You may be able to find a solution in the wiki. Otherwise, open an issue.

Contributions

MatlabStan Copyright (c) 2017 Brian Lau [email protected], BSD-3

PSIS package Copyright (c) 2015 Aki Vehtari, GPL-3

Please feel free to fork and contribute!




鲜花

握手

雷人

路过

鸡蛋
该文章已有0人参与评论

请发表评论

全部评论

专题导读
热门推荐
阅读排行榜

扫描微信二维码

查看手机版网站

随时了解更新最新资讯

139-2527-9053

在线客服(服务时间 9:00~18:00)

在线QQ客服
地址:深圳市南山区西丽大学城创智工业园
电邮:jeky_zhao#qq.com
移动电话:139-2527-9053

Powered by 互联科技 X3.4© 2001-2213 极客世界.|Sitemap