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

Value

A list with components

adj: This multiplier adjusts the posterior odds for k vs k-1 gene models
var: An estimate of the variance of adj
coef: Posterior means of coefficients
loc: Marginal Posterior for location for k gene model
hk.ratio.mean: argh! I need to look this up

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
...: unused

Author

Charles C. Berry cberry@ucsd.edu

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.