subsample_lm: K-fold Resampled Coefficient Estimation for Linear Regression

In cNORM: Continuous Norming

K-fold Resampled Coefficient Estimation for Linear Regression

Description

Performs k-fold resampling to estimate averaged coefficients for linear regression. The coefficients are averaged across k different subsets of the data to provide more stable estimates. For small samples (n < 100), returns a standard linear model instead.

Usage

subsample_lm(text, data, weights, k = 10)

Arguments

text	A character string or formula specifying the model to be fitted
data	A data frame containing the variables in the model
weights	Optional numeric vector of weights. If NULL, unweighted regression is performed
k	Integer specifying the number of resampling folds (default = 10)

Details

The function splits the data into k subsets, fits a linear model on k-1 subsets, and stores the coefficients. This process is repeated k times, and the final coefficients are averaged across all iterations to provide more stable estimates.

Value

An object of class 'lm' with averaged coefficients from k-fold resampling. For small samples, returns a standard lm object.

cNORM documentation built on Nov. 4, 2024, 5:07 p.m.