Create MCMC chains derived from previously sampled values
Create MCMC chains derived from previously sampled values
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 ET=Eexp(Y).
NMixChainsDerived(object)
Arguments
object: an object of class NMixMCMC or NMixMCMClist
Returns
An object of the same class as argument object. When object was of class NMixMCMC, the resulting object contains additionally the following components: - chains.derived: a data.frame with columns labeled expy.Mean.1, , expy.Mean.p containing the sampled values of Eexp(Y[1]), , Eexp(Y[p]).
summ.expy.Mean: posterior summary statistics for Eexp(Y[1]), , Eexp(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.