vcov.gkwreg: Extract Variance-Covariance Matrix from a Generalized...

In gkwreg: Generalized Kumaraswamy Regression Models for Bounded Data

Extract Variance-Covariance Matrix from a Generalized Kumaraswamy Regression Model

Description

This function extracts the variance-covariance matrix of the estimated parameters from a fitted Generalized Kumaraswamy regression model. The variance-covariance matrix is essential for statistical inference, including hypothesis testing and confidence interval calculation.

Usage

## S3 method for class 'gkwreg'
vcov(object, complete = TRUE, ...)

Arguments

object	An object of class "gkwreg", typically the result of a call to gkwreg.
complete	Logical indicating whether the complete variance-covariance matrix should be returned in case some coefficients were omitted from the original fit. Currently ignored for gkwreg objects.
...	Additional arguments (currently not used).

Details

The variance-covariance matrix is estimated based on the observed information matrix, which is derived from the second derivatives of the log-likelihood function with respect to the model parameters. For gkwreg objects, this matrix is typically computed using the TMB (Template Model Builder) automatic differentiation framework during model fitting.

The diagonal elements of the variance-covariance matrix correspond to the squared standard errors of the parameter estimates, while the off-diagonal elements represent the covariances between pairs of parameters.

Value

A square matrix with row and column names corresponding to the coefficients in the model. If the variance-covariance matrix is not available (for example, if the model was fitted with hessian = FALSE), the function returns NULL with a warning.

See Also

gkwreg, confint, summary.gkwreg

gkwreg documentation built on April 16, 2025, 1:10 a.m.