expvariog.fn: Internal function used to estimate the variance and range...

In ProbForecastGOP: Probabilistic weather forecast using the GOP method

Description

Internal function called by the Variog.fit and ProbForecastGOP functions when fitting an exponential theoretical variogram to an empirical variogram via the method of Weighted Least Squares when the estimate of the nugget effect is held fixed.

Usage

expvariog.fn(v,variog,d,w)

Arguments

v	numeric vector with the variance and range parameters of the exponential variogram.
variog	numeric vector giving the values of the empirical variogram at distances given by the numeric vector d.
d	numeric vector giving the distances (or the bin midpoints) at which the empirical variogram has been computed.
w	numeric vector giving the weights to be used in the Weighted Least Squares, that is, the number of pairs of meteorological stations with distance falling in any given bin.

Details

This function is an internal function that is used and called by the Variog.fit and ProbForecastGOP functions to estimate the parameters of an exponential variogram when fitting to an empirical variogram via Weighted Least Squares, keeping the nugget effect fixed. - Defaults -

None.

Value

The function returns the weighted least-square loss function relative to the empirical variogram and the theoretical exponential variogram evaluated for a given set v of variance and range parameters. This is the function that is minimized to obtain estimates of the variance and range parameters of the exponential variogram, when the nugget effect is held fixed.

Author(s)

Berrocal, V. J. [e-mail], Gel, Y., Raftery, A. E., Gneiting, T.

ProbForecastGOP documentation built on May 2, 2019, 3:42 a.m.