Generates points from a Neyman-Scott point process using parameters provided by the user.
A named vector containing the values of the parameters of the process that generates the points.
A matrix with two columns, corresponding to the upper and lower limits of each dimension, respectively.
A character string indicating the distribution of
children around their parents. Use
The distribution of the number of children
generated by a randomly selected parent. For a Poisson
A list of further information that is required about the distribution for the number of children generated by parents. See ‘Details’.
For a list of possible parameter names, see fit.ns.
"child.info" argument is required when
is set to
"twoplane". It must be a list that comprises (i) a
w, providing the halfwidth of the detection
zone; (ii) a component named
b, providing the halfwidth of
the survey area; (iii) a component named
l, providing the
time lag between planes (in seconds); and (iv) a component named
tau, providing the mean dive-cycle duration. See Stevenson,
Borchers, and Fewster (in prep) for details.
A list. The first component gives the Cartesian coordinates of the generated points. A second component may provide sibling information.
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set.seed(1234) ## One-dimensional Thomas process. data.thomas <- sim.ns(c(D = 10, lambda = 5, sigma = 0.025), lims = rbind(c(0, 1))) ## Fitting a model to these data. fit.thomas <- fit.ns(data.thomas$points, lims = rbind(c(0, 1)), R = 0.5) ## Three-dimensional Matern process. data.matern <- sim.ns(c(D = 10, lambda = 10, tau = 0.1), disp = "uniform", lims = rbind(c(0, 1), c(0, 2), c(0, 3))) ## Fitting a model to these data. fit.matern <- fit.ns(data.matern$points, lims = rbind(c(0, 1), c(0, 2), c(0, 3)), R = 0.5, disp = "uniform")
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