model.fit: Computation of parametric variogram model In ProbForecastGOP: Probabilistic weather forecast using the GOP method

Description

Internal function used and called by the Variog.fit and the ProbForecastGOP functions to fit a parametric variogram model to an empirical variogram.

Usage

 `1` ```model.fit(par.model,emp.variog,max.dist.fit,init.val,init.var,fix.nugget) ```

Arguments

 `par.model` character string giving the name of the parametric model to fit to the empirical variogram. Implemented models are exponential, spherical, gauss, gencauchy, and matern. `emp.variog` an object of the class emp.variog, output of the function `Emp.variog` or of the function `avg.variog`. `max.dist.fit` number giving the maximum distance considered when fitting the variogram. `init.val` numeric vector giving the initial values for the parameters. The number of initial values to be entered depends on the variogram model specified. `init.var` number giving an initial estimate for the variance parameter of the variogram. `fix.nugget` logical field indicating whether the nugget should be considered fixed or not. If TRUE the nugget effect will be assumed to be constant, and a value for the fixed nugget effect can be also provided. If the value provided is different from the one entered in the init.val field, then the value of the nugget effect is taken to be the one entered in the init.val field.

Details

The function estimates the parameters in the variogram model by minimizing the weighted least-square loss function.

- Defaults -

None.

Value

The function returns a numeric vector with the estimates of the parameters of the parametric variogram model fitted to the empirical variogram.

Author(s)

Berrocal, V. J. (veroberrocal@gmail.com), Raftery, A. E., Gneiting, T., Gel, Y.

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