modeP {MasterBayes} | R Documentation |
Finds the mode of the posterior marginal distribution of parents
modeP(postP, threshold=0, ...)
postP |
posterior distribution of parentage |
threshold |
threshold probability under which ML parents are replaced by NA |
... |
further arguments to be passed |
Individuals that do not have a parent assignment with a posterior probability exceeding the threshold
, or whose parents belong to the base or unsampled population. Please bear in mind that the mode of the marginal distribution write_postP="MARGINAL"
may be different from the mode of the joint distribution write_postP="JOINT"
. For example the male that has the highest marginal probability (marginal with respect to potential mothers) may not be the male that is in the parental category (i.e. dam/sire combination) with the highest probability. The mode of the joint distribution is marginal with respect to other offspring and with multigenerational pedigrees may not coincide with the mode of the distribution of pedigrees.
pedigree with id in the first column, and ML estimates for dam and sire in the second and third columns
Jarrod Hadfield j.hadfield@ed.ac.uk
Hadfield J.D. et al, Molecular Ecology
data(WarblerP) data(WarblerG) GdP<-GdataPed(WarblerG) var1<-expression(varPed(c("lat", "long"), gender="Male", relational="OFFSPRING")) # paternity is to be modelled as a function of distance # between offspring and male territories res1<-expression(varPed("offspring", restrict=0)) # indivdiuals from the offspring generation are excluded as parents res2<-expression(varPed("terr", gender="Female", relational="OFFSPRING", restrict="==")) # mothers not from the offspring territory are excluded PdP<-PdataPed(formula=list(var1,res1,res2), data=WarblerP, USsire=FALSE) tP<-tunePed(beta=30) model1<-MCMCped(PdP=PdP, GdP=GdP, tP=tP, nitt=3000, thin=2, burnin=1000) ped<-modeP(model1$P, threshol=0.9) ped