R: Dependent Gaussian Processes for Longitudinal Correlated Factors

# Dependent Gaussian Processes for Longitudinal Correlated Factors

## Documentation for package ‘DGP4LCF’ version 1.0.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

factor_loading_heatmap | Displaying significant factor loadings in the heatmap.
factor_score_trajectory | Plotting figures for factor score trajectory.
gibbs_after_mcem_algorithm | Generating posterior samples for parameters (other than DGP parameters) in the model and predicted gene expression for one chain.
gibbs_after_mcem_combine_chains | Combining from all chains the posterior samples for parameters in the model and predicted gene expressions.
gibbs_after_mcem_diff_initials | Generating different initials for multiple chains.
gibbs_after_mcem_load_chains | Loading the saved posterior samples for parameters in the model and predicted gene expressions.
mcem_algorithm | Monte Carlo Expectation Maximization (MCEM) algorithm to return the Maximum Likelihood Estimate (MLE) of DGP Parameters.
mcem_cov_plot | Visualizing cross-correlations among factors.
mcem_parameter_setup | Parameters' setup and initial value assignment for the Monte Carlo Expectation Maximization (MCEM) algorithm.
numerics_summary_do_not_need_alignment | Numerical summary for important continuous variables that do not need alignment.
numerics_summary_need_alignment | Numerical summary for factor loadings and factor scores, which need alignment.
sim_fcs_init | Initials values.
sim_fcs_results_irregular_6_8 | Results when people have irregularly observed time points (some 6 while others 8).
sim_fcs_results_regular_8 | Results when people are observed at common 8 time points.
sim_fcs_truth | Truth of simulated data.
subject_specific_objects | Constructing subject-specific objects required for Gibbs sampler (for subjects with incomplete observations only).
table_generator | Generating a table listing all possible combinations of the binary variables for one gene.