Nothing
summary.gv <-
function(object, ...) {
mtest <- mtest.gv(object)
nl <- "\n\r"
cat(nl)
cat(paste("Summary for", deparse(substitute(object)), nl))
cat(nl)
cat(paste("Number of samples: ", ncol(object$x), nl))
cat(paste("Variogram parameters", nl))
cat(paste(" lag: ", round(object$param$lag, 3), nl))
cat(paste(" lag tolerance: ", round(object$param$tol, 3), nl))
cat(paste(" maximum distance:", round(object$param$lmax, 3), nl))
cat(paste(" lags with data: ",
length(object$lag[!is.na(object$lag)]), nl))
cat(paste(" semi-variance summary:", nl))
print(summary(object$gamma))
cat(nl)
if(mtest) {
# calculate R squared for the model
ssres <- sum((object$residuals)**2)
sstot <- sum((object$gamma - mean(object$gamma))**2)
R2 <- 1 - (ssres/sstot)
models <- c("gaussian", "exponential", "spherical", "linear")
cat(paste("Semivariogram with ", models[object$model$type],
" model (R squared = ", round(R2, 4), ")", nl, sep=""))
cat(paste("Model parameters:", nl))
cat(paste(" sill: ", round(object$model$sill, 3), nl))
cat(paste(" range: ", round(object$model$range, 3), nl))
cat(paste(" nugget:", round(object$model$nugget, 3), nl))
if (object$model$type == 4)
cat(paste(" slope:", round(object$model$slope, 3), nl))
} else {
cat(paste("No model found.", nl))
}
}
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