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DataFusionGDM (version 1.3.2)

besmi_iterative_imputation: Iterative imputation with MICE (tails-chain)

Description

Iterative imputation with MICE (tails-chain)

Usage

besmi_iterative_imputation(
  M_input,
  M_mask,
  M_real = NULL,
  method = "lasso.norm",
  max_iterations = 5,
  imputation_convergence_threshold = 0.001,
  propagation_convergence_threshold = 0.001,
  distance_metric = "mae",
  k = NA,
  bs_i = NA
)

Value

List with final_matrix, metrics, tails_chain

Arguments

M_input

Matrix with NAs to impute

M_mask

Logical mask matrix (TRUE indicates masked positions)

M_real

Optional ground truth matrix

method

MICE method (e.g., 'lasso.norm')

max_iterations

Max outer iterations

imputation_convergence_threshold

Threshold for imputation distance

propagation_convergence_threshold

Threshold for propagation distance

distance_metric

Distance metric name

k

Dataset parameter k (for logging)

bs_i

Bootstrap index (for logging)