Print kriging fit results.

Prints the results from a fitting a spatial process estimate (Krig)

# S3 method for Krig
print(x,digits=4,...)

Arguments

x

Object from Krig function.

digits

Number of significant digits in printed output. Default is 4.

...

Other arguments to print.

Value

Selected summary results from Krig.

See also

print, summary.Krig, Krig

Examples

fit<- Krig(ChicagoO3$x,ChicagoO3$y, aRange=100) 
print(fit) # print the summary 
#> Call:
#> Krig(x = ChicagoO3$x, Y = ChicagoO3$y, aRange = 100)
#>                                              
#>  Number of Observations:                20   
#>  Number of parameters in the null space 3    
#>  Parameters for fixed spatial drift     3    
#>  Model degrees of freedom:              5.4  
#>  Residual degrees of freedom:           14.6 
#>  GCV estimate for tau:                  4.012
#>  MLE for tau:                           3.699
#>  MLE for sigma:                         20.25
#>  lambda                                 0.68 
#>  User supplied sigma                    NA   
#>  User supplied tau^2                    NA   
#> Summary of estimates: 
#>               lambda      trA      GCV   tauHat -lnLike Prof converge
#> GCV        0.9654031 4.842326 22.02399 4.085538     49.16244        4
#> GCV.model         NA       NA       NA       NA           NA       NA
#> GCV.one    0.9654031 4.842326 22.02399 4.085538           NA        4
#> RMSE              NA       NA       NA       NA           NA       NA
#> pure error        NA       NA       NA       NA           NA       NA
#> REML       0.6755001 5.442135 22.11055 4.011747     49.14736        3
fit # this will work too 
#> Call:
#> Krig(x = ChicagoO3$x, Y = ChicagoO3$y, aRange = 100)
#>                                              
#>  Number of Observations:                20   
#>  Number of parameters in the null space 3    
#>  Parameters for fixed spatial drift     3    
#>  Model degrees of freedom:              5.4  
#>  Residual degrees of freedom:           14.6 
#>  GCV estimate for tau:                  4.012
#>  MLE for tau:                           3.699
#>  MLE for sigma:                         20.25
#>  lambda                                 0.68 
#>  User supplied sigma                    NA   
#>  User supplied tau^2                    NA   
#> Summary of estimates: 
#>               lambda      trA      GCV   tauHat -lnLike Prof converge
#> GCV        0.9654031 4.842326 22.02399 4.085538     49.16244        4
#> GCV.model         NA       NA       NA       NA           NA       NA
#> GCV.one    0.9654031 4.842326 22.02399 4.085538           NA        4
#> RMSE              NA       NA       NA       NA           NA       NA
#> pure error        NA       NA       NA       NA           NA       NA
#> REML       0.6755001 5.442135 22.11055 4.011747     49.14736        3