feature_cor: High dimensional imputation via batch processed chained...

In pdwaggoner/hdImpute: A Batch Process for High Dimensional Imputation

High dimensional imputation via batch processed chained random forests Build correlation matrix

Description

High dimensional imputation via batch processed chained random forests Build correlation matrix

Usage

feature_cor(data, return_cor)

Arguments

data	A data frame or tibble.
return_cor	Logical. Should the correlation matrix be printed? Default set to FALSE.

Value

A cross-feature correlation matrix

References

Waggoner, P. D. (2023). A batch process for high dimensional imputation. Computational Statistics, 1-22. doi: <10.1007/s00180-023-01325-9>

van Buuren S, Groothuis-Oudshoorn K (2011). "mice: Multivariate Imputation by Chained Equations in R." Journal of Statistical Software, 45(3), 1-67. doi: <10.18637/jss.v045.i03>

Examples

## Not run: 
feature_cor(data = data, return_cor = FALSE)

## End(Not run)

pdwaggoner/hdImpute documentation built on Sept. 2, 2024, 6:41 a.m.