varcov {bqtl}  R Documentation 
Create a moment matrix of the marker variables and of the regressors by the phenotype variable. For use in regression modelling on the markers.
varcov(x, ana.obj, partial=NULL, scope,...)
x 
A formula to specify the dependent and independent variables
to be used in subsequent calculations e.g 
ana.obj 
An 
partial 
A formula whose right hand side specifies variables to be treated as covariates. 
scope 
Usually not explicitly used. Optional vector of variable names. 
... 
ignored 
This is just a wrapper for make.varcov
.
A list with components
var.x 
Moment matrix of the marker regressor variables 
cov.xy 
Moment matrix of the marker regressor variables versus the phenotype variable 
var.y 
The Second central moment of the phenotype variable 
df 
The degrees of freedom, when no variables are specified in

It is generally NOT a good idea to do regressions on
illconditioned designs using the moment matrices. The
excuse for doing so here is twofold. First, calculations using this
method are used to perform importance sampling, so minor numerical
inaccuracies in computing the probabilites used in sampling get
straightened out by the importance weights. Second, it will typically
be the case that a prior is set on the regression coefficients and
this results in a positive constant (aka a 'ridge' parameter) being
added to diagonal of varcov()$var.x
and this reduces the
illconditioning. Of course the rational for using the method is to
speed the sampling, and it is very effective at doing so.
Charles C. Berry cberry@ucsd.edu
The examples in swap
and twohk
.