reg: Regression Matrix

In NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

Regression Matrix

Description

Computes regression such that one variable is regressed over all other variables

Usage

reg(
  data,
  family = c("binomial", "gaussian", "Gamma", "poisson"),
  symmetric = TRUE
)

Arguments

data	A dataset
family	Error distribution to be used in the regression model. Defaults to "logistic". Set to any family used in function family
symmetric	Should matrix be symmetric? Defaults to TRUE, taking the mean of the two edge weights (i.e., [i,j] and [j,i]) Set to FALSE for asymmetric weights (i.e., [i,j] does not equal [j,i])

Value

A matrix of fully regressed coefficients where one variable is regressed over all others

Author(s)

Alexander Christensen <[e-mail]>

Examples

#binarize responses
psyb <- ifelse(neoOpen>=4, 1, 0)

## Not run: 
#perform logistic regression
mat <- reg(psyb)
## End(Not run)

NetworkToolbox documentation built on June 8, 2025, 11:40 a.m.