"summary.krig.image" <-
function (x, digits = 4, ...) 
{
    summary <- list(call = x$call, num.observation = length(x$residuals), 
        enp = x$trace, nt = x$nt, res.quantile = quantile(x$residuals, 
            seq(0, 1, 0.25)), shat.MLE = x$shat.MLE, shat.GCV = x$shat.GCV, 
        rhohat = x$rhohat, m = 2, lambda = x$lambda, cost = x$cost, 
        rho = x$rho, sigma2 = x$sigma2)
    class(summary) <- "summary.krig.image"
    summary$covariance <- cor(x$fitted.values * sqrt(x$weights), 
        (x$y) * sqrt(x$weights))^2
    hold <- (sum((x$y - mean(x$y))^2) - sum(x$residuals^2))/(sum((x$y - 
        mean(x$y))^2))
    summary$adjr2 <- 1 - ((length(x$residuals) - 1)/(length(x$residuals) - 
        x$eff.df)) * (1 - hold)
    summary$digits <- digits
    summary$cov.function <- as.character(x$call$cov.function)
    summary$correlation.model <- FALSE
    summary
}