get_cs_correlation: Get Correlations Between CSs, using Variable with Maximum PIP...

In susieR: Sum of Single Effects Linear Regression

Get Correlations Between CSs, using Variable with Maximum PIP From Each CS

Description

This function evaluates the correlation between single effect CSs. It is not part of the SuSiE inference. Rather, it is designed as a diagnostic tool to assess how correlated the reported CS are.

Usage

get_cs_correlation(model, X = NULL, Xcorr = NULL, max = FALSE)

Arguments

model	A SuSiE fit, typically an output from susie or one of its variants.
X	n by p matrix of values of the p variables (covariates) in n samples. When provided, correlation between variables will be computed and used to remove CSs whose minimum correlation among variables is smaller than min_abs_corr.
Xcorr	p by p matrix of correlations between variables (covariates). When provided, it will be used to remove CSs whose minimum correlation among variables is smaller than min_abs_corr.
max	When max = FAFLSE, return a matrix of CS correlations. When max = TRUE, return only the maximum absolute correlation among all pairs of correlations.

Value

A matrix of correlations between CSs, or the maximum absolute correlation when max = TRUE.

susieR documentation built on March 7, 2023, 6:11 p.m.