design.bib {agricolae} | R Documentation |
Creates Randomized Balanced Incomplete Block Design. "Random" uses the methods of number generation in R. The seed is by set.seed(seed, kinds).
design.bib(trt, k, r=NULL, serie = 2, seed = 0, kinds = "Super-Duper", maxRep=20,randomization=TRUE)
trt |
Treatments |
k |
size block |
r |
Replications |
serie |
number plot, 1: 11,12; 2: 101,102; 3: 1001,1002 |
seed |
seed |
kinds |
method for to randomize |
maxRep |
repetition maximum |
randomization |
TRUE or FALSE - randomize |
The package AlgDesign is necessary.
if r = NULL, then it calculates the value of r smaller for k defined. In the case of r = value, then the possible values for "r" is calculated
K is the smallest integer number of treatments and both values are consistent in design.
kinds <- c("Wichmann-Hill", "Marsaglia-Multicarry", "Super-Duper", "Mersenne-Twister", "Knuth-TAOCP", "user-supplied", "Knuth-TAOCP-2002", "default" )
parameters |
Design parameters |
statistics |
Design statistics |
sketch |
Design sketch |
book |
Fieldbook |
Felipe de Mendiburu
1. Experimental design. Cochran and Cox. Second edition. Wiley Classics Library Edition published 1992
2. Optimal Experimental Design with R. Dieter Rasch, Jurgen Pilz, Rob Verdooren and Albrecht Gebhardt. 2011 by Taylor and Francis Group, LLC CRC Press is an imprint of Taylor and Francis Group, an Informa business.
3. Design of Experiments. Robert O. Kuehl. 2nd ed., Duxbury, 2000.
design.ab
, design.alpha
,design.split
,
design.crd
, design.cyclic
, design.dau
,
design.graeco
, design.lattice
, design.lsd
,
design.rcbd
, design.strip
library(agricolae) # 4 treatments and k=3 size block trt<-c("A","B","C","D") k<-3 outdesign<-design.bib(trt,k,serie=2,seed =41,kinds ="Super-Duper") # seed = 41 print(outdesign$parameters) book<-outdesign$book plots <-as.numeric(book[,1]) matrix(plots,byrow=TRUE,ncol=k) print(outdesign$sketch) # write in hard disk # write.csv(book,"book.csv", row.names=FALSE) # file.show("book.csv")