met: MET analysis

In yzhlinscau/AAfun0s: Added Functions for Echidna

MET analysis

Description

met.plot plots MET data.met.corr calculates var/cov/corr from echidna MET factor analytic results to further research the relation of trial sites. met.biplot This function biplots MET factor analytic results from echidna to find the relation of trial sites and the best variety suitable to trial sites.

Usage

met.plot(data, plot.title = NULL,...)

met.corr(object,siteV,kN=NULL,horiz=TRUE,rotate=FALSE)

met.biplot(object,siteV,biplot=FALSE, dSco.u=NULL,dLam.u=NULL)

met.vmat(object,siteV,VmatN,corN)

Arguments

data	MET data.
plot.title	MET plot title.
object	echidna factor analytic results for MET, such as mm.
siteV	trial site values, a vector or data frame.
horiz	output cluster site result format, horiz(default).
rotate	Rotate the factor loadings, FALSE(default).
biplot	output biplots, FALSE(default).
dSco.u	Least score of Variety breeding value.
dLam.u	Least distance from center.
kn	Site cluster group numbers, 3(default).

Author(s)

Yuanzhen Lin <[e-mail]>

References

Yuanzhen Lin. R & ASReml-R Statistics. China Forestry Publishing House. 2016

Examples

## Not run: 
library(AFEchidna)

path="C:/Users/echi/exam" #home
setwd(path)

MET<-read.csv('MET.csv')
names(MET)

# example 1
# variable order: yield,genotype,site,row,col
MET2<-MET[,c(9,1,2,4:5)] 
str(MET2)
met.plot(MET2)

# example 2
MET3<-MET[,c(9,1,2,4:7)] # add variable order on MET2: Rep, Block
str(MET3)
met.plot(MET3,"My met trials")

## running met analysis with FA model
mm<-echidna(es0.file="MET.es0",trait='yield',fixed='Loc',
      random='Genotype.xfa2(Loc)',
      residual='sat(Loc).units', #sat(Loc).ar1(Col).ar1(Row)
      #predict=c('Genotype'),
      vpredict=c('V Vmat Genotype.xfa1(Loc)','R cor 20:40'),
      qualifier='!maxit 50 !SLN',
      foldN='mm',
      met=T)
      
Var(mm)

siteV<-unique(MET['Loc']) # should be a data.frame or vector

met.corr(mm,siteV=siteV)

met.biplot(mm,siteV=siteV)
met.biplot(mm,siteV=siteV,biplot=T)
met.biplot(mm,siteV=siteV,biplot=T,dSco=1.0,dLam=0.8)

res2<-met.vmat(mm,siteV=siteV,VmatN='Vmat',corN='cor')
res2$res
res2$var


## End(Not run)

yzhlinscau/AAfun0s documentation built on April 18, 2023, 4:11 p.m.