startPed {MasterBayes} | R Documentation

## startPed Object

### Description

An object containing the starting parameterisation of a model, and logical variables indicating wether parameters should be estimated or fixed at the starting parameterisation. By default the starting parameterisation is obtained through a mixture of Maximum Likelihood and heuristic techniques.

### Usage

    startPed(id=NULL, G=NULL, estG=TRUE, A=NULL, estA=TRUE, E1=NULL,
       estE1=TRUE, E2=NULL, estE2=TRUE, dam=NULL,sire=NULL, estP=TRUE,
       beta=NULL, estbeta=TRUE,  USdam=NULL, estUSdam=TRUE,
       USsire=NULL, estUSsire=TRUE, ...)

### Arguments

`id` | vector of indivual id's for `G`, `dam` and `sire`
`G` | list of genotype objects
`estG` | logical; should genotypes be estimated?
`A` | list of allele frequencies
`estA` | logical; should base-population allele frequencies be estimated?
`E1` | vector of allelic dropout rates (default=0.005)
`estE1` | logical; should allelic dropout rates be estimated?
`E2` | vector of stochastic genotyping error rates (default=0.005)
`estE2` | logical; should stochastic error rates be estimated?
`dam` | vector of dam's. If the dam is unknown use `NA`. All dam's must be in `id`
`sire` | vector of sire's. If the sire is unknown use `NA`. All sire's must be in `id`
`estP` | logical; should the pedigree be estimated?
`beta` | vector of population-level parameters
`estbeta` | logical; should the population-level parameters be estimated?
`USdam` | vector of unsampled female population sizes
`estUSdam` | logical; should the female population sizes be estimated?
`USsire` | vector of unsampled male population sizes
`estUSsire` | logical; should the male population sizes be estimated?
`...` |

### Details

If `estG=FALSE` an approximation is used for genotyping error. In this case error rates and allele frequencies are not estimated but fixed at the starting parameterisation. If indivdiuals have been typed more than once, then the approxiamtion only uses the genotype that first appears in the `GdP$G` object passed to `MCMCped`. If `A` is not specified estimates are taken directly from `GdP$G` using `extractA`. If `E1` and `E2` are not specified they are set to 0.005. Note that if the approximation for genotyping error is used Wang's (2005) model is not used, and the CEVUS model (Marshall 1998) is adopted. In this case `E2` is the per-allele error rate and `E2`(2-`E2`) is the per-genotype error rate used by CERVUS. If `dam` and `sire` are not specified the most likely set of parents given the genetic data are used (see `MLE.ped`). The starting value of `beta`, if not given, is the MLE of beta given the starting pedigree (see `MLE.beta`). The starting values of `USdam` and `USsire`, if not given, are the MLE based on the genotype data (see `MLE.popsize`).

### Value

list containing the arguments passed

### Author(s)

Jarrod Hadfield j.hadfield@sheffield.ac.uk

### See Also

`MCMCped`

### Examples

    # In this example we simulate a pedigree and then fix the
    # pedigree and estimate the population level paarmeters

    data(WarblerP)

    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=TRUE))

    # mothers not from the offspring territory are excluded

    PdP<-PdataPed(formula=list(var1,res1,res2), data=WarblerP, USsire=FALSE)
    simped<-simpedigree(PdP, beta=-0.25)

    # simulate a pedigree where paternity drops with distance (beta=-0.25)

    sP<-startPed(dam=simped$ped[,2], sire=simped$ped[,3], estP=FALSE)
    model1<-MCMCped(PdP=PdP, sP=sP, nitt=3000, thin=2, burnin=1000)
    plot(model1$beta)

    # The true underlying value is -0.25

[Package MasterBayes version 2.0 Index]