A layered multiple importance sampling scheme for focused optimal Bayesian experimental design

https://arxiv.org/abs/1903.11187

Build and Install

$ git clone --recursive https://github.com/chi-feng/LMIS-OED.git

Eigen sources are included as a submodule. If you cloned the repository without the submodules, you can get them with the command

$ git submodule update --init

Prerequisites to build (on Ubuntu/Debian)

$ sudo apt install build-essential cmake

Run build.sh to produce build artifacts in build/

Example

./build/Driver -experiment mossbauer -dim 3 -index 0 -poi 1 -sigeps 0.4 -design -1.3,0,1.3 -N 100 -M1 100 -M2 100 -useMIS 1 -outfile test.txt

• -index 0 means the parameter of interests has index 0
• -poi 1 means only one parameter of interest.

Running analysis code

Uses python2.7. Some python packages are required to run analysis code: numpy, matplotlib