RMark: MS_popan – R documentation

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MS_popan

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))),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)
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

R Code for Mark Analysis

v2.2.7

GPL (>= 2)

Authors

Jeff Laake <jefflaake@gmail.com> with code contributions from Eldar Rakhimberdiev, Ben Augustine, Daniel Turek and Brett McClintock and example data and analysis from Bret Collier, Jay Rotella, David Pavlacky, Andrew Paul, Luke Eberhart- Phillips, Jake Ivan, and Connor Wood.

Initial release

2019-11-4