Summarize Model Fits

Provides a summary method for the "RiskMap" class that computes the standard errors and p-values for likelihood-based model fits.

Usage

# S3 method for class 'RiskMap'
summary(object, ..., conf_level = 0.95)

object: An object of class "RiskMap" obtained as a result of a call to glgpm.
...: other parameters.
conf_level: The confidence level for the intervals (default is 0.95).

A list containing:

reg_coef: A matrix with the estimates, standard errors, z-values, p-values, and confidence intervals for the regression coefficients.
me: A matrix with the estimates and confidence intervals for the measurement error variance, if applicable.
sp: A matrix with the estimates and confidence intervals for the spatial process parameters.
tau2: The fixed nugget variance, if applicable.
ranef: A matrix with the estimates and confidence intervals for the random effects variances, if applicable.
conf_level: The confidence level used for the intervals.
family: The family of the model (e.g., "gaussian").
kappa: The kappa parameter of the model.
log.lik: The log-likelihood of the model fit.
cov_offset_used: A logical indicating if a covariance offset was used.
aic: The Akaike Information Criterion (AIC) for the model, if applicable.

This function computes the standard errors and p-values for the parameters of a "RiskMap" model, adjusting for the covariance structure if needed.

Handles both Gaussian and non-Gaussian families, and accounts for fixed and random effects in the model.