mcmc-0.2.4: Sample from a posterior using Markov chain Monte Carlo

Copyright(c) Dominik Schrempf 2020
LicenseGPL-3.0-or-later
Maintainerdominik.schrempf@gmail.com
Stabilityunstable
Portabilityportable
Safe HaskellNone
LanguageHaskell2010

Mcmc.Proposal.Slide

Description

Creation date: Wed May 6 10:59:13 2020.

Synopsis

Documentation

slide Source #

Arguments

:: Double

Mean.

-> Double

Standard deviation.

-> String

Name.

-> Int

Weight.

-> Bool

Enable tuning.

-> Proposal Double 

Additive proposal with normally distributed kernel.

slideSymmetric Source #

Arguments

:: Double

Standard deviation.

-> String

Name.

-> Int

Weight.

-> Bool

Enable tuning.

-> Proposal Double 

Additive proposal with normally distributed kernel with mean zero. This proposal is very fast, because the Metropolis-Hastings ratio does not include calculation of the forwards and backwards kernels.

slideUniform Source #

Arguments

:: Double

Delta.

-> String

Name.

-> Int

Weight.

-> Bool

Enable tuning.

-> Proposal Double 

Additive proposal with uniformly distributed kernel. This proposal is very fast, because the Metropolis-Hastings ratio does not include calculation of the forwards and backwards kernels.

slideContrarily Source #

Arguments

:: Double

Mean.

-> Double

Standard deviation.

-> String

Name.

-> Int

Weight.

-> Bool

Enable tuning.

-> Proposal (Double, Double) 

Additive proposal with normally distributed kernel.

The two values are slid contrarily so that their sum stays constant. Contrary proposals are useful when parameters are confounded.