readZ: Read the structure and explain it

In CorReg: Linear Regression Based on Linear Structure Between Variables

Description

This function describes the structure of sub-regression given by an adjacency matrix. It computes the associated regression coefficients and R-squared for each sub-regression.

Usage

readZ(
  Z = Z,
  B = NULL,
  crit = c("none", "R2", "F", "sigmaX"),
  varnames = NULL,
  output = c("index", "names", "all"),
  X = NULL,
  order = 1
)

Arguments

Z	binary adjacency matrix of the structure (size p)
B	is the complete structure (Z with sub-regression coefficients instead of 1 and an additional first line for the intercepts)
crit	define the criterion to use: c("none","R2","F","sigmaX")
varnames	the names of the variables (size p)
output	indicates the content of the output: c("index","names","all")
X	is a data frame or matrix containing the dataset
order	define the order used (0: none, -1: decreasing, 1: growing) for printing

Value

a list containing the sub-regressions details. Each item of the list represents a subregression. First element is the R-square.Second element is the variable that is regressed by others. Then comes the list of the explicative variables in the subgression and the associated coefficients (in the first column).

Examples

data <- mtcars
# we first search a sub-regression structure
res <- structureFinder(X = data, nbini = 30, verbose = 0)
# then we can try to interpret it
readZ(Z = res$Z_opt, crit = "R2", output = "all", X = data)
# each component is a sub-regression
# First line: The adjusted R-squared is given
# Second line: the name of the covariate that is regressed by others
# other lines: Coefficients of sub-regression and name of the associated covariate

CorReg documentation built on Feb. 20, 2020, 5:07 p.m.