logDenGaussian: logDenGaussian

In twDEMC: parallel DEMC

Description

Invokes the model and calculate an unnormalized logDensity (-1/2*misfit) assuming (multivariate) Gaussian errors in both data in priors.

Usage

logDenGaussian(theta,
 logDenAccept = numeric(0), metropolisStepTemp = c(parms = 1), 
    ..., fModel, theta0 = theta, obs, invCovar, thetaPrior = NULL, 
    invCovarTheta = NULL, namesTheta = NULL, blockIndices = NULL, 
    scale = -1/2)

Arguments

theta	the parameter vector to be optimized (may be more than updated, if used with blocks).
logDenAccept	scalar: logDen for parms from revious run for two step Metropolis decision
metropolisStepTemp	numeric named vector: the temperature for internal metropolis step
...	any other arguments passed to fModel
fModel	the model function, which predicts the output based on theta
theta0	parameter vector, first argument to fModel. Before invocation components theta overwrite theta0
obs	vector of data to compare with
invCovar	the inverse of the Covariance of obs (its uncertainty) << alternatively a vector of variances (diagonal covariance matrix) can be supplied and calculation is much more efficient
thetaPrior	the prior estimate of the parameters
invCovarTheta	the inverse of the Covariance of the prior parameter estimates << alternatively a vector of variances (diagonal covariance matrix) can be supplied and calculation is much more efficient
namesTheta	names assigned to theta (if not NULL), before invoking mofModel
blockIndices	integer vector: index of the components in theta and theta0 that should be regarded in this block
scale	factor to mulitply the misfit (e.g. -1/2 to obtain the unnormalized logDensity)

Details

If thetaPrior is not specified (NULL) then no penalty is assigned to parameters.

Supports a two-step Metropolis descision. If logDenAccept["parms"] is provided, then a Metropolis descision is done based only on the parameters. If it fails, then c(obs=NA, parms=-Inf) is returned. The possible costly evaluation of fModel is avoided.

Value

the misfit: scale *( t(tmp.diffObs) %*% invCovar %*% tmp.diffObs + t(tmp.diffParms) %*% invCovarTheta %*% tmp.diffParms )

Author(s)

Thomas Wutzler

See Also

twDEMCBlockInt dummyTwDEMCModel

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