View source: R/simSpatialDSte.R
simSpatialDSte | R Documentation |
This simulates line transect distance sampling data with a spatial distribution of objects in a heterogeneous landscape where the parameter beta controls the effect of habitat. Multiple sample occasions are simulated and temporary emigration is allowed (parameter phi). Habitat is simulated according to a Gaussian random field model defined within the function. Uses a half normal detection model (if perp = TRUE) or a Gaussian hazard model (perp = FALSE).
To recreate the data sets used in the book with R 3.6.0 or later, include sample.kind="Rounding"
in the call to set.seed
. This should only be used for reproduction of old results.
simSpatialDSte(nsites=28, dim=10, beta=1, lam0=2.5, nsurveys=4, sigma=3,
phi=0.6, theta=2, show.plots=3)
nsites |
number of sites |
dim |
number of pixels along each side of the square site |
beta |
the effect of habitat on the number of individuals in a pixel. |
lam0 |
expected population size at each site |
nsurveys |
the number of replicate surveys |
sigma |
scale of half-normal detection function |
phi |
probability an individual is available for detection, ie, not temporarily emigrated. |
theta |
exponential correlation in the spatial covariate. |
show.plots |
the number of sites for which plots should be displayed; set to 0 to suppress plotting. |
A list with the values of the input arguments and the following additional elements:
npixels |
the number of pixels in each site (= dim^2) |
B |
distance from line to edge of square (= dim/2) |
M |
true number of individuals at each site |
d |
perpendicular distance of each pixel from the line |
Habitat |
pixels x sites matrix, value of habitat covariate for each pixel |
y |
sites x pixels x surveys array, number of animals detected |
Counts |
sites x surveys matrix, number of animals detected (summed over pixels) |
Mizel et al (2018) Appendix S1, based in turn on Kéry & Royle (2016).
Kéry, M. & Royle, J.A. (2016) Applied Hierarchical Modeling in Ecology.
Mizel, J.D., Schmidt, J.H., & Lindberg, M.S. (2018) Accommodating temporary emigration in spatial distance sampling models. Journal of Applied Ecology, 55, 1456-1464.
Kéry, M. & Royle, J.A. (2021) Applied Hierarchical Modeling in Ecology AHM2 - 11.
# Run the function with default values and look at the output
str(tmp <- simSpatialDSte())
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