Source for "Hierarchical expectation propagation for Bayesian aggregation of average data"

NOTE: These codes accompany an outdated version of the manuscript hosted as v1 of the arXiv publication linked below. Please refer to the updated codes for an improved approach under (https://github.com/wds15/baad)[https://github.com/wds15/baad]. This hep repository will likely be retired some time soon.

Date: February 1st, 2016

This repository includes the R and Stan source files used to generate the main outputs in our paper on Bayesian aggregation of average data.

The code is distributed under the BSD-3 license, see LICENSE.

Please refer to our newer (and improved) version of the method and cite our work when you use these codes or apply our approach:

S. Weber, A. Gelman, B. Carpenter, D. Lee, M. Betancourt, A. Vehtari, A. Racine (2016), "Hierarchical expectation propagation for Bayesian aggregation of average data", arXiv:1602.02055

To use the code, we recommend to start with one of the examples below as template and modify it to your needs.

Updates will be posted to https://github.com/wds15/hep

Contents

• extrap_linear.R Linear example
• extrap_logistic.R Logistic example
• extrap_pkpd.R Non-linear PK/PD example
• extrap_ep_routine.R Main EP routine
• utils.R Various utility functions

News

2016-02-01: Initial release. 2020-05-14: Add note about newer version.

Software used

R session info:

R version 3.1.3 (2015-03-09)
Platform: x86_64-unknown-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server release 6.5 (Santiago)

locale:
[1] C

attached base packages:
[1] methods   stats     graphics  grDevices utils     datasets  base     

other attached packages:
 [1] assertthat_0.1 abind_1.4-0    loo_0.1.2      arm_1.8-4      lme4_1.1-7    
 [6] Matrix_1.1-5   MASS_7.3-39    rstan_2.7.0    inline_0.3.13  Rcpp_0.11.6   

loaded via a namespace (and not attached):
 [1] BH_1.58.0-1         RcppEigen_0.3.2.3.0 StanHeaders_2.7.0  
 [4] coda_0.17-1         codetools_0.2-10    grid_3.1.3         
 [7] lattice_0.20-31     matrixStats_0.14.2  minqa_1.2.4        
[10] nlme_3.1-120        nloptr_1.0.4        parallel_3.1.3     
[13] splines_3.1.3       stats4_3.1.3        tools_3.1.3