DAU.test: Finding the Variance Analysis of the Augmented block Design In agricolae: Statistical Procedures for Agricultural Research

 DAU.test 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

F. de Mendiburu

References

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

`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)
``````

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.