ccF: Multiple comparison: Calinski and Corsten

In ExpDes: Experimental Designs Package

Description

ccF Performs the Calinski and Corsten test based on the F distribution.

Usage

ccF(y, trt, DFerror, SSerror, alpha = 0.05, group = TRUE, main = NULL)

Arguments

y	Numeric or complex vector containing the response varible.
trt	Numeric or complex vector containing the treatments.
DFerror	Error degrees of freedom.
SSerror	Error sum of squares.
alpha	Significance of the test.
group	TRUE or FALSE.
main	Title.

Value

Multiple means comparison for the Calinski and Corsten test.

Author(s)

Eric B Ferreira, [e-mail]

Patricia de Siqueira Ramos

Daniel Furtado Ferreira

References

CALI\'NSKI, T.; CORSTEN, L. C. A. Clustering means in ANOVA by Simultaneous Testing. Biometrics. v. 41, p. 39-48, 1985.

Examples

data(ex2)
attach(ex2)
rbd(trat, provador, aparencia, quali = TRUE, mcomp='ccf',
sigT = 0.05, sigF = 0.05)

ExpDes documentation built on Oct. 5, 2021, 9:09 a.m.