MLE.beta: Maximum Likelihood Estimation of Beta
In MasterBayes: ML and MCMC Methods for Pedigree Reconstruction and Analysis

MLE.beta

R Documentation

Maximum Likelihood Estimation of Beta

Description

Finds MLE for beta given a pedigree, via a call to optim. Beta is the paramater vector of a multinomial log-linear model.

Usage

MLE.beta(X.list, ped, beta=NULL, nUSdam=NULL, nUSsire=NULL, shrink=NULL)

Arguments

`X.list`	list of design matrices for each offspring derived using `getXlist`
`ped`	pedigree with id, dam and sire in ech column
`beta`	optional starting vector for beta
`nUSdam`	optional number of unsampled females. Only required if unsampled females have known phenotype.
`nUSsire`	optional number of unsampled males. Only required if unsampled males have known phenotype.
`shrink`	optional scalar for the variance defining the ridge-regression likelihood penalisation.

Value

`beta`	vector of MLE's for beta
`C`	large sample variance-covariance matrix of beta MLE's

Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

References

Hadfield J.D. et al (2006) Molecular Ecology 15 3715-31 Smouse P.E. et al (1999) Journal of Evolutionary Biology 12 1069-1077

Examples

## Not run: 
data(WarblerP)
data(WarblerG)

GdP<-GdataPed(WarblerG)

res1<-expression(varPed("offspring", restrict=0))
var1<-expression(varPed(c("lat", "long"), gender="Male", 
  relational="OFFSPRING"))
res2<-expression(varPed("terr", gender="Female", relational="OFFSPRING",
  restrict="=="))

PdP<-PdataPed(formula=list(var1,res1,res2), data=WarblerP, USsire=FALSE)

X.list<-getXlist(PdP=PdP, GdP=GdP, E2=0.005)

ped<-MLE.ped(X.list)$P
beta<-MLE.beta(X.list, ped) 
beta

## End(Not run)

MasterBayes documentation built on June 22, 2022, 5:06 p.m.