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 fit.gg ). |
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 , data frame or matrix
containing the gene expression measurements used to fit the model. |
groups |
If x is of type ExpressionSet ,
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.
List with the following components:
xnew |
Matrix of length(nsel) rows and
length(groupsnew) columns with observations drawn from the
posterior predictive. |
dnew |
Matrix with same dimensions as xnew with with expression patterns drawn from the posterior. |
anew |
Matrix with same dimensions as xnew with with shape
parameters drawn from the posterior. |
lnew |
Matrix with same dimensions as xnew with with mean
expression drawn from the posterior. |
David Rossell
Rossell D. GaGa: a simple and flexible hierarchical model for microarray data analysis. http://rosselldavid.googlepages.com.
checkfit
for posterior predictive plot,
sim.gg
for prior predictive simulation.