View source: R/simDemoDynocc_AHM2_4.R
simDemoDynocc | R Documentation |
Function to simulate detection/nondetection data under a variant of the demographic occupancy (or 'local survival') model of Roth & Amrhein (2010). Data are simulated in an 'unconditional' manner, i.e., for each site from first to last year. All parameters can be made year-dependent by specification of a range within which annual values will be drawn from uniform distributions.
simDemoDynocc(nsites = 100, nyears = 10, nvisits = 5, psi1 = 0.6,
range.phi = c(0.2, 0.9), range.r = c(0, 0.4), range.p = c(0.1, 0.9),
show.plot=TRUE)
nsites |
Number of sites. |
nyears |
Number of years (or 'seasons', as they are somewhat confusingly often called in the occupancy literature). |
nvisits |
Number of replicate surveys (= occasions) within a year. |
psi1 |
occupancy probability in first year. |
range.phi |
bounds of uniform distribution from which annual local probability of persistence is randomly drawn. |
range.r |
bounds of uniform distribution from which annual local probability of colonization is randomly drawn. |
range.p |
bounds of uniform distribution from which annual probability of detection is randomly drawn. |
show.plot |
If TRUE, plots of results are displayed; set to FALSE if running simulations. |
A list with the values of the arguments input and the following additional elements:
phi |
persistence for each interval, a vector of length nyears - 1 |
r |
colonization for each interval, a vector of length nyears - 1 |
p |
detection probability for each year, a vector of length nyears |
z |
true occurrence state, a nsites x nyears matrix of 0/1 |
y |
the observed detection history, a nsites x nvisits x nyears array |
f |
year of first detection, a vector of length nsites |
nocc.true |
the true number of occupied sites, a vector of length nyears |
nocc.true |
the observed number of occupied sites, a vector of length nyears |
Marc Kéry & Andy Royle
Roth, T. & Amrhein, V. (2010), Estimating individual survival using territory occupancy data on unmarked animals. Journal of Applied Ecology, 47, 386-392.
Kéry, M. & Royle, J.A. (2021) Applied Hierarchical Modeling in Ecology AHM2 - 4.
# Generate data with the default arguments and look at the structure:
str(data <- simDemoDynocc() ) # Implicit defaults
str(data <- simDemoDynocc(psi1 = 1)) # All sites initially occupied
str(data <- simDemoDynocc(nsites = 1000)) # Plenty more sites
str(data <- simDemoDynocc(nyears = 100)) # Plenty more years
str(data <- simDemoDynocc(nvisits = 20)) # Plenty more visits
str(data <- simDemoDynocc(range.phi = c(0.8, 0.8))) # Constant survival
str(data <- simDemoDynocc(range.phi = c(0.2,0.3), range.r = c(0,0.2))) # Decline
str(data <- simDemoDynocc(range.phi = c(0.8,1), range.r = c(0.5,0.7))) # Increase
str(data <- simDemoDynocc(nvisits = 1)) # Single visit
str(data <- simDemoDynocc(range.p = c(1,1))) # Perfect detection
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