R: Summarize Model Fits

summary.RiskMap {RiskMap}

R Documentation

Summarize Model Fits

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

## 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).

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

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.

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