simDM {AHMbook}R Documentation

Simulate count data under the dynamic N-mixture model of Dail-Madsen

Description

Simulation for multiple-visit data (from pcountOpen help file in package unmarked). simDM0 has no covariates while simDM allows for covariates. Both functions assume constant time intervals between primary periods.

Usage

simDM0(nsites = 50, nsurveys = 3, nyears = 5,
  lambda = 4, gamma = 1.5, phi = 0.8, p = 0.7, show.plots=TRUE)

simDM(nsites = 50, nsurveys = 3, nyears = 5,
  mean.lambda = 4, mean.gamma.rel = 0.5,
  mean.phi = 0.8, mean.p = 0.7,
  beta.lam = 1, beta.gamma = 1, beta.phi = -1, beta.p = -1,
  show.plots=TRUE)

Arguments

nsites

number of sites.

nsurveys

number of replicate (secondary) samples within period of closure.

nyears

number of primary samples: years, seasons etc.

lambda

Initial expected abundance.

gamma

recruitment rate.

phi

apparent survival rate.

p

detection probability.

mean.lambda

Initial expected abundance at cov.lam = 0.

mean.gamma.rel

recruitment rate at cov.gamma = 0.

mean.phi

apparent survival rate at cov.phi = 0.

mean.p

detection probability at cov.p = 0.

beta.lam

the slope of parameter lambda (link transformed) on the cov.lam covariate

beta.gamma

the slope of parameter gamma (link transformed) on the cov.gamma covariate

beta.phi

the slope of parameter phi (link transformed) on the cov.phi covariate

beta.p

the slope of parameter p (link transformed) on the cov.p covariate

show.plots

if TRUE, plots are produced. Set this to FALSE when running simulations.

Value

For simDM0, a list with the values of the input arguments and the following additional elements:

N

true number of individuals, nsites x nyears

S

number of survivors, nsites x (nyears-1)

R

number of recruits, nsites x (nyears-1)

y

number detected, nsites x nyears x nsurveys

yy

number detected as a matrix, nsites x (nyears*nsurveys)

simDM has the following additional elements:

cov.lam

covariate for lambda generated from Uniform(-1, 1), nsites vector

cov.gamma

covariate for gamma generated from Uniform(-1, 1), nsites vector

cov.phi

covariate for phi generated from Uniform(-1, 1), nsites vector

cov.p

covariate for p generated from Uniform(-1, 1), nsites x nyears x nsurveys

ccov.p

cov.p formatted as a matrix, nsites x (nyears*nsurveys)

Author(s)

Marc Kéry & Andy Royle, based in part on code written by Richard Chandler.

References

Dail, D. & Madsen, L. (2011) Models for estimating abundance from repeated counts of an open metapopulation. Biometrics, 67, 577-587.

Kéry, M. & Royle, J.A. (2021) Applied Hierarchical Modeling in Ecology AHM2 - 2.5.

Examples

# Simulate a data set with the default arguments and look at the structure of the output:
tmp0 <- simDM0()
str(tmp0)

tmp <- simDM()
str(tmp)


[Package AHMbook version 0.2.3 Index]