
Find model parameters from models with special components
Source:R/find_parameters_other.R
find_parameters.averaging.Rd
Returns the names of model parameters, like they typically
appear in the summary()
output.
Usage
# S3 method for averaging
find_parameters(x, component = c("conditional", "full"), flatten = FALSE, ...)
# S3 method for betareg
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
# S3 method for DirichletRegModel
find_parameters(
x,
component = c("all", "conditional", "precision", "location", "distributional",
"auxiliary"),
flatten = FALSE,
...
)
# S3 method for mjoint
find_parameters(
x,
component = c("all", "conditional", "survival"),
flatten = FALSE,
...
)
# S3 method for glmx
find_parameters(
x,
component = c("all", "conditional", "extra"),
flatten = FALSE,
...
)
Arguments
- x
A fitted model.
- component
Should all predictor variables, predictor variables for the conditional model, the zero-inflated part of the model, the dispersion term or the instrumental variables be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variable (so called fixed-effects regressions). May be abbreviated. Note that the conditional component is also called count or mean component, depending on the model.
- flatten
Logical, if
TRUE
, the values are returned as character vector, not as list. Duplicated values are removed.- ...
Currently not used.
Value
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.
Examples
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_parameters(m)
#> $conditional
#> [1] "(Intercept)" "wt" "cyl" "vs"
#>