print: Printing objects of classes defined in the SpatialExtreme...

In SpatialExtremes: Modelling Spatial Extremes

Description

Methods for printing objects of classes introduced by the SpatialExtremes package.

Usage

## S3 method for class 'pspline2'
print(x, ...)
## S3 method for class 'maxstab'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'copula'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'spatgev'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'latent'
print(x, digits = max(3, getOption("digits") - 3), ...,
 level = 0.95)

Arguments

x	An object of class 'pspline', 'maxstab', 'copula', 'spatgev' or 'latent'. Most often, x will be the output of one of the following functions: rbpspline, fitmaxstab, fitcopula, fitspatgev or latent.
digits	The number of digits to be printed.
...	Other options to be passed to the print function.
level	A numeric giving the significance level for the credible intervals—class 'latent' only.

Value

Print several information on screen.

Author(s)

Mathieu Ribatet

Examples

##Define the coordinates of each location
n.site <- 30
coord <- matrix(5 + rnorm(2*n.site, sd = sqrt(2)), ncol = 2)
colnames(coord) <- c("lon", "lat")

##Simulate a max-stable process - with unit Frechet margins
data <- rmaxstab(30, coord, cov.mod = "whitmat", nugget = 0, range = 3,
smooth = 0.5)

## Printing max-stable objects
fit <- fitmaxstab(data, coord, "whitmat")
fit

## Printing spatial GEV objects
loc.form <- scale.form <- shape.form <- y ~ 1
fit <- fitspatgev(data, coord, loc.form, scale.form, shape.form)
fit

Example output

        Estimator: MPLE 
            Model: Schlather 
         Weighted: FALSE 
   Pair. Deviance: 111972.1 
              TIC: 112151.5 
Covariance Family: Whittle-Matern 

Estimates
  Marginal Parameters:
  Assuming unit Frechet.

  Dependence Parameters:
 nugget    range   smooth  
0.04921  1.84479  0.88114  

Standard Errors
 nugget    range   smooth  
0.02344  1.04298  0.46304  

Asymptotic Variance Covariance
        nugget      range       smooth    
nugget   0.0005493  -0.0198192   0.0090895
range   -0.0198192   1.0878147  -0.4585356
smooth   0.0090895  -0.4585356   0.2144079

Optimization Information
  Convergence: successful 
  Function Evaluations: 110 

      Model: Spatial GEV model
   Deviance: 4081.846 
        TIC: 4142.756 

    Location Parameters:
locCoeff1  
    1.034  
       Scale Parameters:
scaleCoeff1  
      1.034  
       Shape Parameters:
shapeCoeff1  
       1.15  

Standard Errors
  locCoeff1  scaleCoeff1  shapeCoeff1  
     0.1375       0.2340       0.1844  

Asymptotic Variance Covariance
             locCoeff1  scaleCoeff1  shapeCoeff1
locCoeff1    0.018903   0.028810     0.005307   
scaleCoeff1  0.028810   0.054749     0.026440   
shapeCoeff1  0.005307   0.026440     0.033986   

Optimization Information
  Convergence: successful 
  Function Evaluations: 114 

SpatialExtremes documentation built on Sept. 1, 2020, 3:01 a.m.