gibbs_after_mcem_algorithm function

Generating posterior samples for parameters (other than DGP parameters) in the model and predicted gene expression for one chain.

gibbs_after_mcem_algorithm(
  chain_index,
  mc_num,
  burnin,
  thin_step,
  pathname,
  pred_indicator = FALSE,
  pred_time_index = NULL,
  x,
  mcem_parameter_setup_result,
  mcem_algorithm_result,
  gibbs_after_mcem_diff_initials_result
)

Arguments

• chain_index: A numeric scalar. Index of the chain.
• mc_num: A numeric scalar. Number of iterations in the Gibbs sampler.
• burnin: A numeric scalar. Number of iterations to be discarded as 'burn-in'.
• thin_step: A numeric scalar. This function will only save every 'thin_step'th iteration results in the specified directory to reduce storage space needed. Note that this number can be different from that used in the function 'mcem_algorithm'.
• pathname: A character. The directory where the saved Gibbs samplers are stored.
• pred_indicator: A logical value. pred_indicator = TRUE denotes the need to predict gene expression at new time points. The default value is FALSE.
• pred_time_index: Only needed if pred_indicator = TRUE. Index of the new time points in the full time vector.
• x: A list of n elements. Each element is a matrix of dimension (p, q_i), storing the gene expression observed at q_i time points for the ith subject.
• mcem_parameter_setup_result: A list of objects returned from the function 'mcem_parameter_setup'.
• mcem_algorithm_result: A list of objects returned from the function 'mcem_algorithm'.
• gibbs_after_mcem_diff_initials_result: A list of objects returned from the function 'gibbs_after_mcem_diff_initials'.

Returns

Posterior samples for parameters (other than DGP parameters) in the model and predicted gene expression for one chain.

Details

This function corresponds to Algorithm 2: Step 1 in the main manuscript; therefore reader can consult the paper for more explanations.

Examples

# See examples in vignette
vignette("bsfadgp_regular_data_example", package = "DGP4LCF")
vignette("bsfadgp_irregular_data_example", package = "DGP4LCF")