latent_operation_row: Operation to conduct in the latent space for each row

In udellgroup/mixedgcImp: Missing value imputation for mixed data through Gaussian copula

Operation to conduct in the latent space for each row

Description

operation for each latent row

Usage

latent_operation_row(
  task,
  z,
  lower,
  upper,
  d_index,
  dcat_index,
  corr,
  cat_input = NULL,
  trunc_method = "Iterative",
  n_sample = 5000,
  n_update = 1,
  n_MI = 1
)

Arguments

task	Task to perform. One of "em", "fillup", "sample".
z	A row of Z
lower	A row of Lower
upper	A row of Upper
d_index	Boolean vector with TRUE at ordinal dimensions
dcat_index	Boolean vector with TRUE at categorical dimensions
corr	Current copula correlation estimate
cat_input	Input for categorical dimensions
trunc_method	Method for evaluating truncated normal moments: 'Iterative' or 'Sampling'.
n_sample	Number of MC samples, only used when trunc_method is 'Sampling'
n_update	The number of updates, only used when trunc_method is 'Iterative'

Value

A list containing

loglik

Available when task = 'em'. The average log-likelihood.

Z

Available when task = 'em'. Incomplete Z with updated observed ordinal entries

Zimp

Available when task = 'em' or task == 'fillup' . Complete Z with observed entries the same as Z and missing entries imputed

Zimp_sample

Available when task = 'sample'. Multiple imputation samples.

C

Available when task = 'em'. The conditional co-variance due to missingness

var_ordinal

Available when task = 'em' or task = 'fillup'. The conditional variance due to truncation, i.e. Var(z|a < z < b)

udellgroup/mixedgcImp documentation built on Jan. 25, 2023, 7:55 p.m.