Currently, this function creates chains for marginal means
of exp(data) from previously sampled values (see NMixMCMC).
This is useful in survival context when a density
of \(Y=\log(T)\) is modelled using the function
NMixMCMC and we are interested in inference
on \(\mbox{E}T = \mbox{E}\exp(Y)\).
NMixChainsDerived(object)An object of the same class as argument object. When
object was of class NMixMCMC, the resulting object
contains additionally the following components:
a data.frame with columns labeled
expy.Mean.1, ..., expy.Mean.p containing the
sampled values of \(\mbox{E}\exp(Y_1)\), ...,
\(\mbox{E}\exp(Y_p)\).
posterior summary statistics for \(\mbox{E}\exp(Y_1)\), ..., \(\mbox{E}\exp(Y_p)\).
When object was of the class NMixMCMClist then each of
its components (chains) is augmented by new components
chains.derived and summ.expy.Mean.
an object of class NMixMCMC or NMixMCMClist
Arnošt Komárek arnost.komarek@mff.cuni.cz
NMixMCMC.