Prediction function for the fitted deepspat_ext object
# S3 method for deepspat_MSP
summary(object, newdata, uncAss = TRUE, edm_emp = NULL, ...)A list with the following components:
A matrix of rescaled spatial coordinates produced by scaling the input locations.
A matrix of warped spatial coordinates. For family = "power_stat" this equals srescaled, while for family = "power_nonstat"
the coordinates are further transformed through additional layers.
A numeric value representing the fitted spatial range parameter, computed as exp(logphi_tf).
A numeric value representing the fitted smoothness parameter, computed as 2 * sigmoid(logitkappa_tf).
A numeric matrix giving the estimated covariance matrix of the
dependence parameters \(\psi = (\phi, \kappa)\), computed via the
pairwise likelihood / WLS sandwich-type estimator. NULL if
uncAss = FALSE.
a deepspat object obtained from fitting a deep compositional spatial model for extremes using max-stable processes.
a data frame containing the prediction locations.
assess the uncertainty of dependence parameters or not
empirical estimates of extremal dependence measure for weighted least square inference method
currently unused