Control the Generation of Random Numbers for Sampling from the Proposal Distribution


The functions mvt.sampler and 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 latpos models.


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.