insight (version 0.19.11)

find_parameters.averaging: Find model parameters from models with special components

Description

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,
  ...
)

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.

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.

Examples

data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_parameters(m)