ccF {ExpDes}

Multiple comparison: Calinski and Corsten

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)