resampling.model: Resampling for linear models

In agricolae: Statistical Procedures for Agricultural Research

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)

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