summary.adj: Summarize Laplace approximations

Description

The linear approximations of swap are much improved by the use a Laplace approximations for loci that are not markers. This function combines the results of a call like bqtl(y~configs(swap.obj),...) with the data in swap.obj to provide improved posteriors, et cetera

Usage

## S3 method for class 'adj':
summary(object, n.loc, coef.znames, mode.names=c("add",
"dom"), imp.denom=NULL, swap.obj=NULL)

Arguments

object

Typically, this is the result of a call like bqtl(y~configs(swap.obj),...)

n.loc

The number of genes in this model

coef.znames

map.names for the sample space

mode.names

NULL except for "F2", in which case it is uusally c("add","dom")

imp.denom

Optional, and only used when some sampling scheme other than the default MCMC generates object

swap.obj

The result of a call to swap

Value

A list with components
adjThis multiplier adjusts the posterior odds for k vs k-1 gene models
varAn estimate of the variance of adj
coefPosterior means of coefficients
locMarginal Posterior for location for k gene model
hk.ratio.meanargh! I need to look this up

synopsis

summary.adj(object, n.loc, coef.znames, mode.names=c("add", "dom"), imp.denom=NULL, swap.obj=NULL,...)

Details

There are a lot of details. This sections nneds to be revised to reflect them.

References

Berry C.C. (1998) Computationally Efficient Bayesian QTL Mapping in Experimental Crosses. ASA Proceedings of the Biometrics Section, 164-169.