Simulated draws from model coefficients
Simulate draws from a statistical model to return a data frame of estimates.
simulate_model(model, iterations = 1000, ...)
## S3 method for class 'glmmTMB'
simulate_model(
model,
iterations = 1000,
component = c("all", "conditional", "zi", "zero_inflated", "dispersion"),
verbose = FALSE,
...
)model |
Statistical model (no Bayesian models). |
iterations |
The number of draws to simulate/bootstrap. |
... |
Arguments passed to or from other methods. |
component |
Should all parameters, parameters for the conditional model,
or for the zero-inflated part of the model be returned? Applies to models
with zero-inflated component. |
verbose |
Toggle warnings and messages. |
simulate_model() is a computationally faster alternative
to bootstrap_model(). Simulated draws for coefficients are based
on a multivariate normal distribution (MASS::mvrnorm()) with mean
mu = coef(model) and variance Sigma = vcov(model).
For models from packages glmmTMB, pscl, GLMMadaptive and
countreg, the component argument can be used to specify
which parameters should be simulated. For all other models, parameters
from the conditional component (fixed effects) are simulated. This may
include smooth terms, but not random effects.
A data frame.
library(parameters)
model <- lm(Sepal.Length ~ Species * Petal.Width + Petal.Length, data = iris)
head(simulate_model(model))
if (require("glmmTMB", quietly = TRUE)) {
model <- glmmTMB(
count ~ spp + mined + (1 | site),
ziformula = ~mined,
family = poisson(),
data = Salamanders
)
head(simulate_model(model))
head(simulate_model(model, component = "zero_inflated"))
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