design.split | R Documentation |

It generates split plot design. "Random" uses the methods of number generation in R. The seed is by set.seed(seed, kinds).

```
design.split(trt1, trt2,r=NULL, design=c("rcbd","crd","lsd"),serie = 2,
seed = 0, kinds = "Super-Duper", first=TRUE,randomization=TRUE)
```

`trt1` |
Treatments in Plots |

`trt2` |
Treatments in Subplots |

`r` |
Replications or blocks |

`design` |
Experimental design |

`serie` |
number plot, 1: 11,12; 2: 101,102; 3: 1001,1002 |

`seed` |
seed |

`kinds` |
method for to randomize |

`first` |
TRUE or FALSE - randomize rep 1 |

`randomization` |
TRUE or FALSE - randomize |

kinds <- c("Wichmann-Hill", "Marsaglia-Multicarry", "Super-Duper", "Mersenne-Twister", "Knuth-TAOCP", "user-supplied", "Knuth-TAOCP-2002", "default" )

`parameters` |
Design parameters |

`book` |
Fieldbook |

Felipe de Mendiburu

Statistical Procedures for Agricultural Research. Kwanchai A. Gomez, Arturo A. Gomez. John Wiley & Sons, new York, 1984

`design.ab`

, `design.alpha`

,`design.bib`

,
`design.crd `

, `design.cyclic `

, `design.dau `

,
`design.graeco`

, `design.lattice`

, `design.lsd`

,
`design.rcbd`

, `design.strip`

```
library(agricolae)
# 4 treatments and 5 blocks in split-plot
t1<-c("A","B","C","D")
t2<-c(1,2,3)
outdesign <-design.split(t1,t2,r=3,serie=2,seed=45,kinds ="Super-Duper")#seed=45
book<-outdesign$book# field book
# write in hard disk
# write.table(book,"book.txt", row.names=FALSE, sep="\t")
# file.show("book.txt")
```

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