View source: R/particlefilter.R
procfun0 | R Documentation |
Simulates effects of process noise following a Gaussian perturbation. Note that process noise only influences positive abundances (i.e. process noise cannot contribute to colonization)
procfun0(sp, xt, inverse = FALSE, time = NULL)
sp |
a numeric vector of length one or two, specifying either the log-transformed standard deviation of the process noise function, or an intercept and slope for calculating variance of process noise based on a power function of x, of the form var=exp(B0)*x^exp(B1) |
xt |
a number or numeric vector of abundances at time t, before process noise has occurred |
inverse |
a logical specifying whether the inverse (i.e. probability of drawing a value of zero given xt and sp) should be calcualted |
time |
the timestep - defaults to NULL (i.e. not used) |
a number or numeric vector of length xt, with predicted abundances after process noise has occurred
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