model.comp: Model comparison for asreml.

In yzhlinscau/AAFMM: Augment Applications in Fitting Mixed Models

Description

model.comp This function would compare models with different random structure under the same fixed factors.

Usage

model.comp(m1=NULL,m2=NULL,Nml=NULL,mulM=NULL,LRT=NULL,rdDF=NULL)

Arguments

m1	Model 1 asreml results,such as "m1.asr".
m2	Model 2 asreml results.
Nml	A vector with more than 2 asreml results, such as "c(m1,m2,m3,m4)".
mulM	mulM is "TRUE" for a vector's comparison with multi-models, default (FALSE).
LRT	Value TRUE for Likelihood ratio test (LRT), default (FALSE) for no LRT.
rdDF	Value TRUE to control Ddf minus 0.5, default FALSE for LRT with Ddf. If TRUE, Ddf would minus 0.5, ie, Ddf=Ddf-0.5.
asrV	asreml version 3(default, V3), or 4 (new version V4).

Author(s)

Yuanzhen Lin <[e-mail]>

References

Yuanzhen Lin. R & ASReml-R Statistics. China Forestry Publishing House. 2016 AAFMM website:https://github.com/yzhlinscau/AAFMM

Examples

## Not run: 

library(AAFMM)
df<-PrSpa

## for ASReml-R V3.0
library(asreml)
fm<-asreml(h5~ 1+Rep,random=~ Fam, 
           subset=Spacing=='3',data=df,maxit=40)

fm1a<-asreml(cbind(dj,h5)~ trait+trait:Rep, 
             random=~ us(trait):Fam, 
             rcov=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)
             
fm1b<-asreml(cbind(dj,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             rcov=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

fm3a<-asreml(cbind(dj,h3,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             rcov=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

fm3b<-asreml(cbind(dj,h3,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             rcov=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

#####   model comparison    #####
model.comp(m1=fm1a,m2=fm1b)
model.comp(m1=fm1a,m2=fm1b,LRT=TRUE)
model.comp(m1=fm1a,m2=fm1b,LRT=TRUE,rdDF=TRUE)

model.comp(Nml=c(fm3a,fm3b,fm1a,fm1b,fm),mulM=TRUE)
model.comp(Nml=c(fm3a,fm3b,fm1a,fm1b,fm),mulM=TRUE,LRT=TRUE)


## for ASReml-R V4.0
library(asreml4)

fm<-asreml(h5~ 1+Rep,random=~ Fam, 
           subset=Spacing=='3',data=df,maxit=40)

fm1a<-asreml(cbind(dj,h5)~ trait+trait:Rep, 
             random=~ us(trait):Fam, 
             residual=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)
             
fm1b<-asreml(cbind(dj,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             residual=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

fm3a<-asreml(cbind(dj,h3,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             residual=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

fm3b<-asreml(cbind(dj,h3,h5)~ trait+trait:Rep, 
             random=~ diag(trait):Fam, 
             residual=~units:us(trait),
             subset=Spacing=='3',data=df,maxit=40)

#####   model comparison    #####
model.comp(m1=fm1a,m2=fm1b,asrV=4)
model.comp(m1=fm1a,m2=fm1b,LRT=TRUE,asrV=4)
model.comp(m1=fm1a,m2=fm1b,LRT=TRUE,rdDF=TRUE,asrV=4)

model.comp(Nml=c(fm3a,fm3b,fm1a,fm1b,fm),mulM=TRUE,asrV=4)
model.comp(Nml=c(fm3a,fm3b,fm1a,fm1b,fm),mulM=TRUE,LRT=TRUE,asrV=4)

## End(Not run)

yzhlinscau/AAFMM documentation built on May 4, 2019, 4:17 a.m.