ccF function

Multiple comparison: Calinski and Corsten

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

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.

Returns

Multiple means comparison for the Calinski and Corsten test.

Examples

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

References

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

Author(s)

Eric B Ferreira, eric.ferreira@unifal-mg.edu.br

Patricia de Siqueira Ramos

Daniel Furtado Ferreira