MasterBayes (version 2.55)

PdataPed: PdataPed Object

Description

PdataPed creates an object of class PdataPed, which typically contains the phenotype data to be passed to MCMCped and the formula that defines the model to be fitted. is.PdataPed returns TRUE if x is of class PdataPed

Usage

PdataPed(formula, data=NULL, id=data$id, sex=data$sex,
   offspring=data$offspring, timevar=data$timevar, 
   USdam=FALSE, USsire=FALSE)

Arguments

formula

list of model predictors of the form expression(varPed(...))

data

data frame containing the predictor variables

id

vector of individual identifiers. If not specified, data must have an id column

sex

vector of individual sexes (either 'Male' or 'Female' or NA). If not specified individuals are assumed to be hermpahroditic unless data has a sex column

offspring

binary vector indicating whether records belong to offspring (1) or not (0)

timevar

an optional vector indicating cohorts for multigenerational pedigree reconstruction

USdam

logical or character; if TRUE a single undiferentaited population of unsampled females exists. If USdam is a character vector it must have the same length as id with factor levels representing sub-populations (in time or space) over which the number of unsampled females vary.

USsire

logical or character; if TRUE a single undiferentaited population of unsampled males exists. If USsire is a character vector it must have the same length as id with factor levels representing sub-populations (in time or space) over which the number of unsampled males vary.

...

further arguments to be passed

Value

list containing the arguments passed

Details

If the number of unsampled individuals varies over subpopulations, and the parentage of an offspring is not restricted to ceratin subpopulations then the parameters will not be idenifiable. This can be resolved by using an informative prior (see priorPed) for the number of unsampled individuals in each sub-population, or using the restrict argument in varPed.

See Also

MCMCped

Examples

# NOT RUN {
id<-1:20
sex<-sample(c("Male", "Female"),20, replace=TRUE)
offspring<-c(rep(0,18),1,1)
lat<-rnorm(20)
long<-rnorm(20)
mating_type<-gl(2,10, label=c("+", "-"))

test.data<-data.frame(id, offspring, lat, long, mating_type, sex)

res1<-expression(varPed("offspring", restrict=0))
var1<-expression(varPed(c("lat", "long"), gender="Male", 
  relational="OFFSPRING"))
var2<-expression(varPed(c("mating_type"), gender="Female", 
  relational="MATE"))
var3<-expression(varPed("mating_type", gender="Male"))

PdP<-PdataPed(formula=list(res1, var1, var2, var3), data=test.data)

# }