swapf2 {bqtl}  R Documentation 
An MCMC sampler for loci using precomputed dispersion matrices, various priors, and a preselected set of variables. For use with F2 intercross design.
Using precomputed dispersion matrices, various priors, and a preselected set of variables, one locus is removed, all other loci are examined to determine the effect of each on the posterior. One locus is sampled. The process is repeated until each locus has been removed and a new one sampled in its place (possibly the same one that was removed is sampled).
swapf2(varcov, invars, rparm, nreps, ana.obj, locs, locs.prior, combo.prior, tol = 1e10)
varcov 
The result of 
rparm 
The 'ridge' parameters for the independent variables  larger values imply more shrinkage or a more concentrated prior for the regresion coefficients. 
nreps 
How many cycles of MCMC to perform 
ana.obj 
A object produced by 
invars 
A vector of variable indexes. This determines which
variables to start in the model. If both additive and
dominance terms are to be used, they should occupy adjacent
locations in 
locs 
The pairs of columns of 
locs.prior 
Vector whose elements are the prior masses to associate with each locus. Typically, these sum to one, but sometimes they might each be set to one (as in computing lod scores). The default value sets them all to 1.0. 
combo.prior 
The prior probability for each term or combination of terms for the phenotypic effect at a locus. Typically, there will be three of these  one for the 'additive' term (linear in number of alleles from one parent strain), the 'dominance' term (quadratic in allele number), or both terms. The default sets them all to 1/3. 
tol 
Used in forming QR decomposition. Let it be. 
A call to swapf2
is used to obtain the results. This function
is really just a wrapper.
A list with components:
configs 
A 2k by k by nreps array of indexes of variables sampled in
each of the nreps iterations. Models using less than 2k variables

posteriors 
A vector of length 
coefs 
A 2k by k by nreps matrix of the regression
coefficients. Models using less than 2k variables

call 
The call to 
cond 
The 
marg 
The 
alt.marginal 
A vector with 
alt.coef 
A vector with 
Charles C. Berry cberry@ucsd.edu
Berry C.C. (1998) Computationally Efficient Bayesian QTL Mapping in Experimental Crosses. ASA Proceedings of the Biometrics Section, 164169.