resampling.model {agricolae} | R Documentation

## Resampling for linear models

### Description

This process consists of finding the values of P-value by means of a re-sampling (permutation) process along with the values obtained by variance analysis.

### Usage

    resampling.model(model,data,k,console=FALSE)

### Arguments

`model` | model in R
`data` | data for the study of the model
`k` | number of re-samplings
`console` | logical, print output

### Value

Model solution with resampling.

### Author(s)

Felipe de Mendiburu

### References

Efron, B., Tibshirani, R. (1993) An Introduction to the Boostrap. Chapman and Hall/CRC Phillip I. Good, (2001) Resampling Methods. Birkhauser. Boston . Basel . Berlin

### See Also

`simulation.model`

### Examples

    #example 1 Simple linear regression
    library(agricolae)
    data(clay)
    model<-"ralstonia ~ days"
    analysis<-resampling.model(model,clay,k=2,console=TRUE)

    #example 2 Analysis of variance: RCD
    data(sweetpotato)
    model<-"yield~virus"
    analysis<-resampling.model(model,sweetpotato,k=2,console=TRUE)

    #example 3 Simple linear regression
    data(Glycoalkaloids)
    model<-"HPLC ~ spectrophotometer"
    analysis<-resampling.model(model,Glycoalkaloids,k=2,console=TRUE)

    #example 4 Factorial in RCD

    data(potato)
    potato[,1]<-as.factor(potato[,1])
    potato[,2]<-as.factor(potato[,2])
    model<-"cutting~variety + date + variety:date"
    analysis<-resampling.model(model,potato,k=2,console=TRUE)

[Package agricolae version 1.2-9 Index]