Compute the exponential variogram.
expvg(p, vg, ...)# S3 method for flossdiff.expvg
predict(object, newdata, ...)
# S3 method for flossdiff.expvg
print(x, ...)
Numeric vector of length equal to that of the d component of vg giving the corresponding exponential variogram values with nugget and range defined by p.
numeric vector of length two. Each component should be positively valued. The first component is the nugget and the second is the range parameter.
A list object with component d giving a numeric vector of distances over which the variogram is to be calculated.
A list object returned by flossdiff using expvg as the variogram model.
Numeric giving the distances over which to use the fitted exponential variogram model to make predictions. The default is to go from zero to the maximum lag distance for a given data set, which is not the usual convention for the generic predict, which usually defaults to operate on the lags used in performing the fit.
Not used.
Eric Gilleland
A very simple function used mainly internally by flossdiff when fitting the exponential variogram to the empirical one, and by the predict, print and summary method functions for lossdiff objects. For those wishing to use a different variogram model than the exponential, use this function and its method functions as a template. Be sure to create predict and print method functions to operate on objects of class “flossdiff.XXX” where “XXX” is the name of the variogram function you write (so, “expvg” in the current example).
Cressie, N. A. (2015) Statistics for Spatial Data. Wiley-Interscience; Revised Edition edition (July 27, 2015), ISBN-10: 1119114616, ISBN-13: 978-1119114611, 928 pp.
lossdiff, flossdiff
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## For examples, see lossdiff and flossdiff
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