updateSigmaByGibbsSamplingInvchisq: updateSigmaByGibbsSamplingInvchisq

Description Usage Arguments Details Value Author(s)

Description

update Variance by sampling from a scaled inverse Chi-square distribution with using prior information on sigma

Usage

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updateSigmaByGibbsSamplingInvchisq(theta, argsFUpdateBlock = NULL, 
    fResid, nu0 = 0, sigma20, ...)

Arguments

theta

numeric vector: current state that is used in density function of the block

argsFUpdateBlock

list with possible component intermediate that will be provided to fResid

fResid

function to calculate residuals between prediction and observations, must return a numeric vector

nu0

weight of prior: equivalent number of observations, defaults to no prior (zero obs)

sigma20

prior estimate of variance, needs to be specified only when giving nu0 different from zero

...

further arguemnts to fResid

Details

Gelman et al., 2003, p.51: Estimating variance with known mean.

See the vignette on unknown observation uncertainty.

Value

list with components

accepted

boolean scalar: if step was accepted

xC

numeric vector: components of position in parameter space that are being updated

intermediate

new intermediate state, if provided by fResid

Author(s)

Thomas Wutzler


twDEMC documentation built on May 2, 2019, 5:38 p.m.