NicholsMSOccupancy: Multi-state occupancy example data

In RMark: R Code for Mark Analysis

Multi-state occupancy example data

Description

An occupancy data set for modelling multi-state data (0,1,2).

Format

A data frame with 40 records for 54 observations (sites) on the following 2 variables.

ch

a character vector containing the presence (state 1), presence (state 2), and absence (0) for each visit to the site, and a "." if the site was not visited

freq

frequency of sites with that history

Details

This is a data set from Nichols et al (2007).

References

Nichols, J. D., J. E. Hines, D. I. MacKenzie, M. E. Seamans, and R. J. Gutierrez. 2007. Occupancy estimation and modeling with multiple states and state uncertainty. Ecology 88:1395-1400.

Examples

# This example is excluded from testing to reduce package check time
# To create the data file use:
# NicholsMSOccupancy=convert.inp("NicholsMSOccupancy.inp")
#
# Create a function to fit the 12 models in Nichols et al (2007).
do.MSOccupancy=function()
{
#  Get the data
   data(NicholsMSOccupancy)
# Define the models; default of Psi1=~1 and Psi2=~1 is assumed
   # p varies by time but p1t=p2t
   p1.p2equal.by.time=list(formula=~time,share=TRUE)  
   # time-invariant p p1t=p2t=p1=p2
   p1.p2equal.dot=list(formula=~1,share=TRUE)    
   #time-invariant p1 not = p2
   p1.p2.different.dot=list(p1=list(formula=~1,share=FALSE),p2=list(formula=~1))  
   # time-varying p1t and p2t
   p1.p2.different.time=list(p1=list(formula=~time,share=FALSE),p2=list(formula=~time)) 
   # delta2 model with one rate for times 1-2 and another for times 3-5; 
   #delta2 defined below
   Delta.delta2=list(formula=~delta2) 
   Delta.dot=list(formula=~1)  # constant delta
   Delta.time=list(formula=~time) # time-varying delta
# Process the data for the MSOccupancy model
   NicholsMS.proc=process.data(NicholsMSOccupancy,model="MSOccupancy")
# Create the default design data
   NicholsMS.ddl=make.design.data(NicholsMS.proc)
# Add a field for the Delta design data called delta2.  It is a factor variable
# with 2 levels: times 1-2, and times 3-5.
   NicholsMS.ddl=add.design.data(NicholsMS.proc,NicholsMS.ddl,"Delta",
     type="time",bins=c(0,2,5),name="delta2")
# Create a list using the 4 p modls and 3 delta models (12 models total)
   cml=create.model.list("MSOccupancy")
# Fit each model in the list and return the results
   return(mark.wrapper(cml,data=NicholsMS.proc,ddl=NicholsMS.ddl,delete=TRUE))
}
# Call the function to fit the models and store it in MSOccupancy.results
MSOccupancy.results=do.MSOccupancy()
# Print the model table for the results
print(MSOccupancy.results)
# Adjust model selection by setting chat=1.74
MSOccupancy.results=adjust.chat(chat=1.74,MSOccupancy.results)
# Print the adjusted model selection results table
print(MSOccupancy.results)
#
# To fit an additive model whereby p1 and p2 differ by time and p2 differs from
# p1 a constant amount on the logit scale, use
#
# p varies by time logit(p1t)=logit(p2t)+constant
p1.plust.p2.by.time=list(formula=~time+p2,share=TRUE) 

RMark documentation built on Aug. 14, 2022, 1:05 a.m.