Find model parameters from models with special components
Returns the names of model parameters, like they typically
appear in the summary() output.
## S3 method for class 'averaging'
find_parameters(x, component = c("conditional", "full"), flatten = FALSE, ...)
## S3 method for class 'betareg'
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
## S3 method for class 'DirichletRegModel'
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
## S3 method for class 'mjoint'
find_parameters(
x,
component = c("all", "conditional", "survival"),
flatten = FALSE,
...
)
## S3 method for class 'glmx'
find_parameters(
x,
component = c("all", "conditional", "extra"),
flatten = FALSE,
...
)x |
A fitted model. |
component |
Which type of parameters to return, such as parameters for the
conditional model, the zero-inflated part of the model, the dispersion
term, the instrumental variables or marginal effects be returned? Applies
to models with zero-inflated and/or dispersion formula, or to models with
instrumental variables (so called fixed-effects regressions), or models
with marginal effects from mfx. May be abbreviated. Note that the
conditional component is also called count or mean
component, depending on the model. There are three convenient shortcuts:
|
flatten |
Logical, if |
... |
Currently not used. |
A list of parameter names. The returned list may have following elements:
conditional, the "fixed effects" part from the model.
full, parameters from the full model.
data(mtcars) m <- lm(mpg ~ wt + cyl + vs, data = mtcars) find_parameters(m)
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