NonParaUpdatePosterior: Updates posteriors from a given nonparametric prior, which...

In markvdwiel/ShrinkBayes: Bayesian analysis of high-dimensional omics data, either Gaussian or counts

Updates posteriors from a given nonparametric prior, which may include a point mass

Description

This function re-computes posteriors for (one class of) parameters from posteriors obtained by FitAllShrink and a new nonparametric prior obtained by NonParaUpdatePrior.

Usage

NonParaUpdatePosterior(fitall, updateoutput, fitall0=NULL, ncpus = 2)

Arguments

fitall	A 2-component list object resulting from FitAllShrink or from CombinePosteriors.
updateoutput	A list object resulting from NonParaUpdatePrior.
fitall0	An optional 2-component list object resulting from FitAllShrink containing the fits under the null-model.
ncpus	Integer. The number of cpus to use for parallel computations.

Details

Rescaling of posteriors is used as described in Van de Wiel et al. (2012).

Value

A list object with the same number of components as the first component of fitall (number of fits), each containing 3-component lists which contain

postbetanon0	List of posteriors (one for each parameter/contrast involved)
postbeta0	Point mass (often zero) mixture proportion
loglik	Marginal log-likelihood

Note

The resulting posteriors are for the main parameter or contrasts of interest only, which should be indicated in the shrinkpara and shrinklc option in NonParaUpdatePrior. Posteriors of other parameters do not alter with respect to those in fitall.

Author(s)

Mark A. van de Wiel

References

Van de Wiel MA, Leday GGR, Pardo L, Rue H, Van der Vaart AW, Van Wieringen WN (2012). Bayesian analysis of RNA sequencing data by estimating multiple shrinkage priors. Biostatistics.

See Also

NonParaUpdatePrior for finding the optimal mixture prior and FitAllShrink for fitting under standard parametric priors. In addition, see MixtureUpdatePosterior for posteriors given a parametric mixture prior.

Examples

#See ShrinkSeq, ShrinkGauss and CombinePosteriors

markvdwiel/ShrinkBayes documentation built on March 27, 2022, 7:47 p.m.