Samples new coeffients via Gibbs sampling in a spectral GP object.

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Description

Samples new coefficients via Gibbs sampling in a spectral GP object following the Gibbs sampling scheme of Wikle (2002), which involves an extra variance component (sig2e and a noisy version of the process (z).

Usage

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## S3 method for class 'gp'
Gibbs.sample.coeff(object, z, sig2e, meanVal=0,
sdVal=1,returnHastings=FALSE, ...)

Arguments

object

A GP object, created by gp.

z

Vector of values for z, the noisy version of the process.

sig2e

Noise variance component that distorts z as a version of the process.

meanVal

Optional mean value for z.

sdVal

Optional standard deviation value for z.

returnHastings

Optional argument telling whether to return the logdensity of the proposal for use in a Metropolis-Hastings correction calculation.

...

Other arguments.

Details

This function can be used in an MCMC context to take Gibbs samples of the process coefficients, as part of the algorithm of Wikle (2002). The function modifies the GP object, updating the coeff and process components.

Value

The function modifies the GP object, which is essentially a pointer (an R environment in this case), so NULL is returned, unless returnHastings=TRUE.

Author(s)

Christopher Paciorek paciorek@alumni.cmu.edu

References

Type 'citation("spectralGP")' for references.

See Also

gp, propose.coeff.gp, updateprocess.gp

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