RMark (version 3.0.0)

mstrata: Multistrata example data

Description

An example data set which appears to be simulated data that accompanies MARK as an example analysis using the Multistrata model.

Format

A data frame with 255 observations on the following 2 variables.

ch

a character vector containing the encounter history of each bird with strata

freq

the number of birds with that capture history

Details

This is a data set that accompanies program MARK as an example for the Multistrata model. The models created by RMark are all "Parm-specific" models by default. The sin link is not allowed because all models are specified via the design matrix. Although you can set links for the parameters, usually the default values are preferable. See make.mark.model for additional help building formula for Psi using the remove.intercept argument.

Examples

 # \donttest{
# This example is excluded from testing to reduce package check time
data(mstrata)
run.mstrata=function()
{
#
# Process data
#
mstrata.processed=process.data(mstrata,model="Multistrata")
#
# Create default design data
#
mstrata.ddl=make.design.data(mstrata.processed)
#
#  Define range of models for S; note that the betas will differ from the output
#  in MARK for the ~stratum = S(s) because the design matrix is defined using
#  treatment contrasts for factors so the intercept is stratum A and the other
#  two estimates represent the amount that survival for B abd C differ from A.
#  You can use force the approach used in MARK with the formula ~-1+stratum which
#  creates 3 separate Betas - one for A,B and C.
#
S.stratum=list(formula=~stratum)
S.stratumxtime=list(formula=~stratum*time)
#
#  Define range of models for p
#
p.stratum=list(formula=~stratum)
#
#  Define range of models for Psi; what is denoted as s for Psi
#  in the Mark example for Psi is accomplished by -1+stratum:tostratum which
#  nests tostratum within stratum.  Likewise, to get s*t as noted in MARK you
#  want ~-1+stratum:tostratum:time with time nested in tostratum nested in
#  stratum.
#
Psi.s=list(formula=~-1+stratum:tostratum)
#
# Create model list and run assortment of models
#
model.list=create.model.list("Multistrata")
#
# Add on specific model that is paired with fixed p's to remove confounding
#
p.stratumxtime=list(formula=~stratum*time)
p.stratumxtime.fixed=list(formula=~stratum*time,fixed=list(time=4,value=1))
model.list=rbind(model.list,c(S="S.stratumxtime",p="p.stratumxtime.fixed",
  Psi="Psi.s"))
#
# Run the list of models
#
mstrata.results=mark.wrapper(model.list,data=mstrata.processed,ddl=mstrata.ddl,threads=2,
                            delete=TRUE)
#
# Return model table and list of models
#
return(mstrata.results)
}
mstrata.results=run.mstrata()
mstrata.results

# Example of reverse Multistratum model
#data(mstrata)
#mod=mark(mstrata,model="Multistrata",delete=TRUE)
#mod.rev=mark(mstrata,model="Multistrata",reverse=TRUE,delete=TRUE)
#Psilist=get.real(mod,"Psi",vcv=TRUE)
#Psilist.rev=get.real(mod.rev,"Psi",vcv=TRUE)
#Psivalues=Psilist$estimates
#Psivalues.rev=Psilist.rev$estimates
#TransitionMatrix(Psivalues[Psivalues$time==1,])
#TransitionMatrix(Psivalues.rev[Psivalues.rev$occ==1,])
# }