An adaptive basin-hopping Markov-chain Monte Carlo algorithm for Bayesian optimisation

## An adaptive basin-hopping Markov-chain Monte Carlo algorithm for Bayesian optimisation

This is the python (v3.7) implementation of the hoppMCMC algorithm aiming to identify and sample from the high-probability regions of a posterior distribution. The algorithm combines three strategies: (i) parallel MCMC, (ii) adaptive Gibbs sampling and (iii) simulated annealing. Overall, hoppMCMC resembles the basin-hopping algorithm implemented in the optimize module of scipy, but it is developed for a wide range of modelling approaches including stochastic models with or without time-delay.

### Contents

1. Prerequisites

2. Linux installation

### 1) Prerequisites

The hoppMCMC algorithm requires the following packages, which are not included in this package:

numpy scipy mpi4py (MPI parallelisation)

The mpi4py package is required for parallelisation; however, it can be omitted.

### 2) Linux installation

1. Easy way:

If you have pip installed, you can use the following command to download and install the package.

pip install hoppMCMC

pip install hoppMCMC-xxx.tar.gz

1. Hard way:

If pip is not available, you can unpack the package contents and perform a manual install.

tar -xvzf hoppMCMC-xxx.tar.gz cd hoppMCMC-xxx python setup.py install

This will install the package in the site-packages directory of your python distribution. If you do not have root privileges or you wish to install to a different directory, you can use the –prefix argument.

python setup.py install –prefix=<dir>

In this case, please make sure that <dir> is in your PYTHONPATH, or you can add it with the following command.

In bash shell:

export PYTHONPATH=<dir>:$PYTHONPATH In c shell: setenv PYTHONPATH <dir>:$PYTHONPATH

### Credits

‘modern-package-template’ - http://pypi.python.org/pypi/modern-package-template

## News

### 1.1

Release date: 13-Sep-2018

• Fixed a bug in reading output (Python 3)

### 1.0

Release date: 30-Jul-2018

• Compatible with Python 3

### 0.6

UNRELEASED

• Print out the covariates in addition to the parameters

### 0.5

Release date: 14-Feb-2017

• Minor improvement on pulsevarUpdate

### 0.4

Release date: 14-Oct-2015

• Fixed an issue with default parameters

### 0.3

Release date: 09-Oct-2015

• This version includes an improvement in compareAUCs

### 0.2

Release date: 28-Sep-2015

• This version includes a documentation and examples

### 0.1

Release date: 28-Sep-2015

• Initial commit

## Project details

Uploaded source