logLm: Log likelihood for mixture model, by marker

Description

The function logLm is used to produce a log likelihood function for one or more traces of DNA, delivering results on a per-marker basis.

Usage

logLm(mixture, presence.only = FALSE, initialize = TRUE)

Value

A function, which takes a mixpar model parameter as argument, and delivers a vector of per-marker loglikelihood values.

Arguments

mixture: A DNAmixture model.
presence.only: Set to TRUE to ignore peak heights and evaluate the likelihood function considering peak presence and absence (heights above and below threshold) only. Defaults to FALSE.
initialize: By default all entered evidence is removed from the networks in object. Setting initialize = FALSE should be done with care, and it is up to the user to ensure that the likelihood being computed is meaningful.

Author

Peter Green (P.J.Green@bristol.ac.uk)

Examples

Run this code

data(test2data)
data(NGMDyes)

## Fit 2-person mixture - baseline model

mixD<-DNAmixture(list(epg),k=2,C=list(0.001),database=db)
pars<-mixpar(rho=list(2),eta=list(100),xi=list(0.1),phi=list(c(U1=0.7,U2=0.3)))
baseline<-logLm(mixD)(pars)

## Fit 2-person mixture model in which contributor 1 is father of a typed individual Cgt 
## with mother Mgt

mixD<-DNAmixture(list(epg),k=2,C=list(0.001),database=db,triangulate=FALSE,compile=FALSE)
rpt.IBD(mixD,,list(Mgt,Cgt)) 
log10LR<-(logLm(mixD)(pars)-baseline)/log(10)
cat('log10 LR',log10LR,' sum:',sum(log10LR),'\n')