Control the Generation of Random Numbers for Sampling from the Proposal Distribution¶
mvnorm.sampler can be used to
fine-tune the construction and sampling from the proposal distribution
in the importance sampling algorithm used in the MCEM algorithm to fit
mvt.sampler(df,fix.seed=TRUE) # Multivariate Student's t-distribution mvnorm.sampler(fix.seed=TRUE) # Multivariate normal distribution
a number, the degrees of freedom of the multivariate Student’s t-distribution.
a logical value; if TRUE the seed of the random number generated is reset in each MCEM iteration to make sure that approximate marginal log-likelihood surface is continuous while the simulation sample size is constant.
Both functions return a list that contains a function to generate random numbers and to compute the log-density function of the distribution from which random numbers are generated.