Last data update: 2014.03.03

R: Class of tensor-product spatial covariances with isotropic...
covIso-classR Documentation

Class of tensor-product spatial covariances with isotropic range

Description

S4 class of isotropic spatial covariance kerlnes based upon the covTensorProduct class

Objects from the Class

In 1-dimension, the covariance kernels are parameterized as in (Rasmussen, Williams, 2006). Denote by theta the range parameter, p the exponent parameter (for power-exponential covariance), s the standard deviation, and h=||x-y||. Then we have C(x,y) = s^2 * k(x,y), with:

Gauss k(x,y) = exp(-1/2*(h/theta)^2)
Exponential k(x,y) = exp(-h/theta)
Matern(3/2) k(x,y) = (1+sqrt(3)*h/theta)*exp(-sqrt(3)*h/theta)
Matern(5/2) k(x,y) = (1+sqrt(5)*h/theta+(1/3)*5*(h/theta)^2)
*exp(-sqrt(5)*h/theta)
Power-exponential k(x,y) = exp(-(h/theta)^p)

Slots

d:

Object of class "integer". The spatial dimension.

name:

Object of class "character". The covariance function name. To be chosen between "gauss", "matern5_2", "matern3_2", "exp", and "powexp"

paramset.n:

Object of class "integer". 1 for covariance depending only on the ranges parameters, 2 for "powexp" which also depends on exponent parameters.

var.names:

Object of class "character". The variable names.

sd2:

Object of class "numeric". The variance of the stationary part of the process.

known.covparam:

Object of class "character". Internal use. One of: "None", "All".

nugget.flag:

Object of class "logical". Is there a nugget effect?

nugget.estim:

Object of class "logical". Is the nugget effect estimated or known?

nugget:

Object of class "numeric". If there is a nugget effect, its value (homogeneous to a variance).

param.n:

Object of class "integer". The total number of parameters.

range.names:

Object of class "character". Names of range parameters, for printing purpose. Default is "theta".

range.val:

Object of class "numeric". Values of range parameters.

Extends

Class "covKernel", directly.

Methods

coef

signature(object = "covIso"): ...

covMat1Mat2

signature(object = "covIso"): ...

covMatrix

signature(object = "covIso"): ...

covMatrixDerivative

signature(object = "covIso"): ...

covParametersBounds

signature(object = "covIso"): ...

covparam2vect

signature(object = "covIso"): ...

vect2covparam

signature(object = "covIso"): ...

covVector.dx

signature(object = "covIso"): ...

inputnames

signature(x = "covIso"): ...

kernelname

signature(x = "covIso"): ...

ninput

signature(x = "covIso"): ...

nuggetflag

signature(x = "covIso"): ...

nuggetvalue

signature(x = "covIso"): ...

show

signature(object = "covIso"): ...

summary

signature(object = "covIso"): ...

Author(s)

O. Roustant, D. Ginsbourger

References

N.A.C. Cressie (1993), Statistics for spatial data, Wiley series in probability and mathematical statistics.

C.E. Rasmussen and C.K.I. Williams (2006), Gaussian Processes for Machine Learning, the MIT Press, http://www.GaussianProcess.org/gpml

M.L. Stein (1999), Interpolation of spatial data, some theory for kriging, Springer.

See Also

km covTensorProduct

Examples

showClass("covIso")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DiceKriging)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DiceKriging/covIso-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: covIso-class
> ### Title: Class of tensor-product spatial covariances with isotropic range
> ### Aliases: covIso-class coef,covIso-method covMat1Mat2,covIso-method
> ###   covMatrix,covIso-method covMatrixDerivative,covIso-method
> ###   covParametersBounds,covIso-method covparam2vect,covIso-method
> ###   vect2covparam,covIso-method covVector.dx,covIso-method
> ###   inputnames,covIso-method kernelname,covIso-method
> ###   ninput,covIso-method nuggetflag,covIso-method
> ###   nuggetvalue,covIso-method nuggetvalue<-,covIso,numeric-method
> ###   show,covIso-method summary,covIso-method
> ### Keywords: classes
> 
> ### ** Examples
> 
> showClass("covIso")
Class "covIso" [package "DiceKriging"]

Slots:
                                                                  
Name:               d           name     paramset.n      var.names
Class:        integer      character        integer      character
                                                                  
Name:             sd2 known.covparam    nugget.flag   nugget.estim
Class:        numeric      character        logical        logical
                                                                  
Name:          nugget        param.n    range.names      range.val
Class:        numeric        integer      character        numeric

Extends: "covKernel"
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>