mean_imp_col: Column Mean Imputation

In slideimp: Numeric Matrices K-NN and PCA Imputation

Column Mean Imputation

Description

Impute missing values in a matrix by replacing them with the mean of their respective columns.

Usage

mean_imp_col(obj, subset = NULL, cores = 1)

Arguments

obj	A numeric matrix with samples in rows and features in columns.
subset	Character. Vector of column names or integer vector of column indices specifying which columns to impute.
cores	Integer. Number of cores for K-NN parallelization (OpenMP). On macOS, OpenMP may need additional compiler configuration.

Value

A numeric matrix of the same dimensions as obj with missing values in the specified columns replaced by column means.

Examples

# Create example matrix with missing values
mat <- matrix(c(1, 2, NA, 4, NA, 6, NA, 8, 9), nrow = 3)
colnames(mat) <- c("A", "B", "C")
mat

# Impute missing values with column means
imputed_mat <- mean_imp_col(mat)
imputed_mat

# Impute only specific columns by name
imputed_subset <- mean_imp_col(mat, subset = c("A", "C"))
imputed_subset

# Impute only specific columns by index
imputed_idx <- mean_imp_col(mat, subset = c(1, 3))
imputed_idx

slideimp documentation built on April 17, 2026, 1:07 a.m.