DAU.test {agricolae}R Documentation

Finding the Variance Analysis of the Augmented block Design

Description

Analysis of variance Augmented block and comparison mean adjusted.

Usage

DAU.test(block, trt, y, method = c("lsd","tukey"),alpha=0.05,group=TRUE,console=FALSE)

Arguments

block

blocks

trt

Treatment

y

Response

method

Comparison treatments

alpha

Significant test

group

TRUE or FALSE

console

logical, print output

Details

Method of comparison treatment. lsd: Least significant difference. tukey: Honestly significant differente. The controls can have different repetitions, at least two, do not use missing data.

Value

means

Statistical summary of the study variable

parameters

Design parameters

statistics

Statistics of the model

comparison

Comparison between treatments

groups

Formation of treatment groups

SE.difference

Standard error of:
Two Control Treatments
Two Augmented Treatments
Two Augmented Treatments(Different Blocks)
A Augmented Treatment and A Control Treatment

vartau

Variance-covariance matrix of the difference in treatments

Author(s)

F. de Mendiburu

References

Federer, W. T. (1956). Augmented (or hoonuiaku) designs. Hawaiian Planters, Record LV(2):191-208.

See Also

BIB.test, duncan.test, durbin.test, friedman, HSD.test, kruskal, LSD.test, Median.test, PBIB.test, REGW.test, scheffe.test, SNK.test, waerden.test, waller.test, plot.group

Examples

library(agricolae)
block<-c(rep("I",7),rep("II",6),rep("III",7))
trt<-c("A","B","C","D","g","k","l","A","B","C","D","e","i","A","B","C","D","f","h","j")
yield<-c(83,77,78,78,70,75,74,79,81,81,91,79,78,92,79,87,81,89,96,82)
out<- DAU.test(block,trt,yield,method="lsd", group=TRUE)
print(out$groups)
plot(out)

[Package agricolae version 1.3-5 Index]