HierAFS: RSM forward regression keeping model hierarchy

In daewr: Design and Analysis of Experiments with R

RSM forward regression keeping model hierarchy

Description

This function performs a hierarchical forward stepwise regression. If an interaction or quadratic term is entered in the model, the parent main effects are also entered into the model.

Usage

HierAFS(y,x,m,c,step) 

Arguments

y	input - this is a vector containing a single numeric column of response data.
x	input - this is a data frame containing the numeric columns of the candidate independent variables. The m three-level factors always preceed the c two-level factors in the design. The factor names or colnames(x) should always be of length (for example letters of the alphabet "A", "B", etc.)
m	input - this is an integer equal to the number of three-level factors in the design
c	input - this is an integer equal to the number of two-level factors in the design. Note m+c must be equal to the number of columns of des.
step	input - this is a single numeric value containing the n umber of steps requested.

Value

returned data frame the first column is a factor variable containing the formula for the model fit at each step, the second numeric column is the R-square statistic for the model fit with each formula.

Author(s)

Gerhard Krennrich, and modified by John Lawson

daewr documentation built on Sept. 9, 2023, 9:06 a.m.