insight (version 0.20.5)

n_parameters: Count number of parameters in a model

Description

Returns the number of parameters (coefficients) of a model.

Usage

n_parameters(x, ...)
# S3 method for default
n_parameters(x, remove_nonestimable = FALSE, ...)
# S3 method for merMod
n_parameters(
  x,
  effects = c("fixed", "random"),
  remove_nonestimable = FALSE,
  ...
)
# S3 method for glmmTMB
n_parameters(
  x,
  effects = c("fixed", "random"),
  component = c("all", "conditional", "zi", "zero_inflated"),
  remove_nonestimable = FALSE,
  ...
)
# S3 method for zeroinfl
n_parameters(
  x,
  component = c("all", "conditional", "zi", "zero_inflated"),
  remove_nonestimable = FALSE,
  ...
)
# S3 method for gam
n_parameters(
  x,
  component = c("all", "conditional", "smooth_terms"),
  remove_nonestimable = FALSE,
  ...
)
# S3 method for brmsfit
n_parameters(x, effects = "all", component = "all", ...)

Value

The number of parameters in the model.

Arguments

x

A statistical model.

...

Arguments passed to or from other methods.

remove_nonestimable

Logical, if TRUE, removes (i.e. does not count) non-estimable parameters (which may occur for models with rank-deficient model matrix).

effects

Should number of parameters for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.

component

Should total number of parameters, number parameters 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.

Examples

data(iris)
model <- lm(Sepal.Length ~ Sepal.Width * Species, data = iris)
n_parameters(model)