NetworkToolbox (version 1.4.2)

reg: 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

Examples

# NOT RUN {
#binarize responses
psyb <- ifelse(neoOpen>=4, 1, 0)

#perform logistic regression
mat <- reg(psyb)

# }