gibbs_after_mcem_algorithm {DGP4LCF}

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

Description

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

Usage

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'.

Details

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

Value

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

Examples

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