| PBIB.test {agricolae} | R Documentation |
Analysis of variance PBIB and comparison mean adjusted. Applied to resoluble designs: Lattices and alpha design.
PBIB.test(block,trt,replication,y,k, method="lsd", alpha=0.05)
block |
blocks |
trt |
Treatment |
replication |
Replication |
y |
Response |
k |
size block |
method |
Comparison treatments |
alpha |
Significant test |
Method of comparison treatment. lsd: least significant difference. tukey: Honestly significant differente.
block |
Vector, consecutive numbers by replication |
trt |
Vector |
replication |
Vector |
y |
numeric vector |
k |
numeric constant |
method |
Character |
alpha |
Numeric |
F. de Mendiburu
1. Iterative Analysis of Generalizad Lattice Designs. E.R. Williams (1977) Austral J. Statistics 19(1) 39-42.
2. Experimental design. Cochran and Cox. Second edition. Wiley Classics Library Edition published 1992
library(agricolae)
library(corpcor)
# alpha design
trt<-1:30
ntr<-length(trt)
r<-2
k<-3
s<-10
obs<-ntr*r
b <- s*r
book<-design.alpha(trt,k,r,seed=5)
book$book[,3]<- gl(20,3)
# dataset
y<-c(5,2,7,6,4,9,7,6,7,9,6,2,1,1,3,2,4,6,7,9,8,7,6,4,3,2,2,1,1,2,
1,1,2,4,5,6,7,8,6,5,4,3,1,1,2,5,4,2,7,6,6,5,6,4,5,7,6,5,5,4)
dbook<-data.frame(book$book,yield=y)
rm(y,trt)
# analysis
attach(dbook)
model <- PBIB.test(block, trt, replication, yield, k=3)
detach(dbook)
# model$comparison
# model$means