CSLMI {DLMRMV}R Documentation

CSLMI: Consensus-based Stochastic Linear Multiple Imputation (Simplified Version)

Description

Performs multiple imputation and parameter estimation using a consensus-based approach. It assumes: - The response variable is in the first column - All other columns are predictors - Missing values are automatically detected - The whole dataset is treated as one block

Usage

CSLMI(data, M)

Arguments

data

Dataframe with response variable in 1st column and predictors in others

M

Number of imputations

Value

A list containing:

Yhat

Matrix of size n x M with imputed response values.

betahat

Average regression coefficients across imputations.

comm

Communication cost (number of messages passed).

Examples

set.seed(123)
data <- data.frame(
  y = c(rnorm(50), rep(NA, 10)),
  x1 = rnorm(60),
  x2 = rnorm(60)
)
result <- CSLMI(data = data, M = 10)
head(result$Yhat)
print(result$betahat)
print(result$comm)

[Package DLMRMV version 0.2.0 Index]