simDM_simDM0: Simulate count data under the dynamic N-mixture model of...

In AHMbook: Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology' Vols 1 and 2

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)

AHMbook documentation built on Aug. 24, 2023, 1:07 a.m.