MS_popan: Convert Multistate data for POPAN-style abundance estimation

In RMark: R Code for Mark Analysis

Convert Multistate data for POPAN-style abundance estimation

Description

Converts data and optionally creates and structures design data list such that population size can be derived with multistate data. Variance estimate is questionable.

Usage

MS_popan(
  x,
  augment_num = 100,
  augment_stratum = "A",
  enter_stratum = "B",
  strata = NULL,
  begin.time = 1,
  groups = NULL,
  ddl = FALSE,
  time.intervals = NULL
)

Arguments

x	an RMark dataframe
augment_num	the number to add with a capture history of all 0s; this is the expected number that were in the population and not ever seen
augment_stratum	the single character to represent outside of the population; use a value not used in the data capture history
enter_stratum	the single character to represent inside of the population but not yet entered; use a value not used in the data capture history
strata	vector of single characters for observed and unobserved states
begin.time	beginning time of observed occasions; two occasions are added to the fron of the capture history at times begin.time-1 and begin.time-2
groups	vector of character variable names of factor variables to use for grouping
ddl	if TRUE, will return processed data and a design data list with the appropriate fixed parameters.
time.intervals	intervals of time between observed occasions

Author(s)

Jeff Laake

Examples

data(dipper)
popan_N=summary(mark(dipper,model="POPAN",
        model.parameters=list(pent=list(formula=~time)),delete=TRUE),se=TRUE)$reals$N
data.list=MS_popan(dipper,ddl=TRUE,augment_num=30)
modMS=mark(data.list$data,data.list$ddl,
        model.parameters=list(Psi=list(formula=~B:toB:time)),brief=TRUE,delete=TRUE)
Psi_estimates=summary(modMS,se=TRUE)$reals$Psi
Nhat_MS=Psi_estimates$estimate[1]*sum(abs(data.list$data$data$freq))
se_Nhat_MS=Psi_estimates$se[1]*Nhat_MS
cat("Popan N = ",popan_N$estimate," (se = ",popan_N$se,")\n")
cat("MS N = ",Nhat_MS," (se = ",se_Nhat_MS,")\n")

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