simData.fn: Simulate count data under a binomial N-mixture model

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

Simulate count data under a binomial N-mixture model

Description

Function to simulate point counts replicated at M sites during J occasions. Population closure is assumed for each site. Expected abundance may be affected by elevation (elev), forest cover (forest) and their interaction. Expected detection probability may be affected by elevation, wind speed (wind) and their interaction. Used in AHM1 to illustrate how a data set under some specific model of interest can be simulated.

Usage

data.fn(M = 267, J = 3, mean.lambda = 2, beta1 = -2, beta2 = 2, beta3 = 1,
   mean.detection = 0.3, alpha1 = 1, alpha2 = -3, alpha3 = 0, show.plot = TRUE)

Arguments

M	Number of spatial replicates (sites)
J	Number of temporal replicates (occasions)
mean.lambda	Mean abundance at value 0 of abundance covariates
beta1	Main effect of elevation on abundance
beta2	Main effect of forest cover on abundance
beta3	Interaction effect on abundance of elevation and forest cover
mean.detection	Mean detection prob. at value 0 of detection covariates
alpha1	Main effect of elevation on detection probability
alpha2	Main effect of wind speed on detection probability
alpha3	Interaction effect on detection of elevation and wind speed
show.plot	if TRUE, plots of the data will be displayed; set to FALSE if you are running simulations

Value

A list with the input arguments and the following additional elements:

elev	Scaled elevation (a vector of length M)
forest	Scaled forest cover (a vector of length M)
wind	Scaled wind speed (an M x J matrix)
lambda	Expected number of individuals at each site (a vector of length M)
N	Realized number of individuals at each site (a vector of length M)
p	Probability of detection for each survey (an M x J matrix)
C	The number of detections for each survey (an M x J matrix)
Ntotal	Total abundance, sum(N)
psi.true	True occupancy in sample
summaxC	Sum of max counts (all sites)
psi.obs	Observed occupancy in sample

Note

The colors used for points in some of the plots indicate different temporal replicates.

Author(s)

Marc Kéry & Andy Royle

References

Kéry, M. & Royle, J.A. (2016) Applied Hierarchical Modeling in Ecology AHM1 - 4.3.

Examples

# Generate a simulated data set with default arguments and look at the structure:
tmp <- data.fn()
str(tmp)

str(data.fn(J = 2))              # Only 2 surveys
str(data.fn(J = 1))              # No temporal replicate
str(data.fn(M = 1, J = 100))     # No spatial replicates, but 100 counts
str(data.fn(beta3 = 1))          # With interaction elev-wind on p
str(data.fn(M = 267, J = 3, mean.lambda = 2, beta1 = -2, beta2 = 2, beta3 = 1,
  mean.detection = 1))           # No obs. process (i.e., p = 1, perfect detection)
str(data.fn(mean.lambda = 50))   # Really common species
str(data.fn(mean.lambda = 0.05)) # Really rare species

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