simnewsamples {gaga} | R Documentation |
Simulates parameters and data from the posterior and posterior predictive distributions, respectively, of a GaGa or MiGaGa model.
simnewsamples(gg.fit, groupsnew, sel, x, groups)
gg.fit |
GaGa or MiGaGa fit (object of type gagafit , as returned by fitGG ). |
groupsnew |
Vector indicating the group that each new sample
should belong to. length(groupsnew) is the number of new
samples that will be generated. |
sel |
Numeric vector with the indexes of the genes we want to draw new samples for (defaults to all genes). If a logical vector is indicated, it is converted to (1:nrow(x))[sel] . |
x |
ExpressionSet , exprSet , data frame or matrix
containing the gene expression measurements used to fit the model. |
groups |
If x is of type ExpressionSet or
exprSet , groups should be the name of the column
in pData(x) with the groups that one wishes to compare. If
x is a matrix or a data frame, groups should be a
vector indicating to which group each column in x
corresponds to. |
The shape parameters are actually drawn from a gamma approximation to
their posterior distribution. The function rcgamma
implements
this approximation.
Object of class 'ExpressionSet'. Expression values can be accessed via
exprs(object)
and the parameter values used to generate the
expression values can be accessed via fData(object)
.
David Rossell
Rossell D. GaGa: a simple and flexible hierarchical model for microarray data analysis. http://rosselldavid.googlepages.com.
checkfit
for posterior predictive plot,
simGG
for prior predictive simulation.