View source: R/simulate_data.R
simulate_data | R Documentation |
simulate_data
conducts a parametric bootstrap to simulate new data and potentially simulate new population dynamics and associated variables
Simulate new data given various potential procedures to propagate uncertainty about parameters.
Using sample_fixed=TRUE
(the default) in sample_variable
is similar to using type=3
in simulate_data
, while
using sample_fixed=TRUE
in sample_variable
is similar to using type=4
in simulate_data
.
Sampling fixed effects will sometimes cause numerical under- or overflow (i.e., output values of NA
) in cases when
variance parameters are estimated imprecisely. In these cases, the multivariate normal approximation being used is a poor
representation of the tail probabilities, and results in some samples with implausibly high (or negative) variances,
such that the associated random effects then have implausibly high magnitude.
simulate_data(fit, type = 1, random_seed = NULL)
fit |
output from |
type |
integer stating what type of simulation to use from the following options:
|
random_seed |
integer passed to |
Report object containing new data and population variables including
New simulated data
Density for each grid cell g, category c, and year y
Index of abundance for each category c, year y, and stratum l
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