Get model parameters from models with special components

Returns the coefficients from a model.

Usage

# S3 method for class 'betareg'
get_parameters(
  x,
  component = c("all", "conditional", "precision", "location", "distributional",
    "auxiliary"),
  ...
)

# S3 method for class 'DirichletRegModel'
get_parameters(
  x,
  component = c("all", "conditional", "precision", "location", "distributional",
    "auxiliary"),
  ...
)

# S3 method for class 'averaging'
get_parameters(x, component = c("conditional", "full"), ...)

# S3 method for class 'glmx'
get_parameters(
  x,
  component = c("all", "conditional", "extra", "location", "distributional", "auxiliary"),
  ...
)

# S3 method for class 'clm2'
get_parameters(x, component = c("all", "conditional", "scale"), ...)

# S3 method for class 'mvord'
get_parameters(
  x,
  component = c("all", "conditional", "thresholds", "correlation"),
  ...
)

# S3 method for class 'mjoint'
get_parameters(x, component = c("all", "conditional", "survival"), ...)

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.

...

Currently not used.

Value

A data frame with three columns: the parameter names, the related point estimates and the component.

Examples

data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
get_parameters(m)
#>     Parameter   Estimate
#> 1 (Intercept) 38.7460642
#> 2          wt -3.2463673
#> 3         cyl -1.3641033
#> 4          vs  0.5241721