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insight (version 0.20.4)

get_parameters.betareg: Get model parameters from models with special components

Description

Returns the coefficients from a model.

Usage

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

# S3 method for glmgee get_parameters(x, component = c("all", "conditional", "dispersion"), ...)

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

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

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

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

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

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

Value

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

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.

Examples

Run this code
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
get_parameters(m)

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