# gboot_cross: Cross-validation bootstrap In geotoolsR: Tools to Improve the Use of Geostatistic

## Description

Performs a boostrap based on error from the cross-validation

## Usage

 1 gboot_cross(data,var,model,B) 

## Arguments

 data object of the class geodata. var object of the class variogram. model object of the class variomodel. B number of the bootstrap that will be performed (default B=1000).

## Details

We can define the error of prediction by ε({s_i})=Z({s_i})-\hat Z({s_i}), where \hat Z({s_i}) are obtained from cross-validation. The steps of the algorithm are:

1. Set {s_i}^*={s_i};

2. Obtain \hat Z({s_i}) from \hat Z({s_i})=∑\limits_{j \ne i}^{n - 1}{{λ _j}Z({s_j})};

3. Calculate ε({s_i})=Z({s_i})-\hat Z({s_i})

4. Sample with replacement ε^*(s_i) from ε (s_i) - \bar ε (s_i);

5. The new data will be Z^*({s_i})=\hat Z({s_i})+ ε^*(s_i);

6. Calculate the new variogram;

7. Calculate and save the statistics of interest;

8. Return to step 4 and repeat the process at least 1000 times.

## Value

variogram_boot gives the variogram of each bootstrap.

variogram_or gives the original variogram.

pars_boot gives the estimatives of the nugget, sill, contribution, range and practical range for each bootstrap.

pars_or gives the original estimatives of the nugget, sill, contribution, range and practical range.

Invalid arguments will return an error message.

## Author(s)

Diogo Francisco Rossoni dfrossoni@uem.br

Vinicius Basseto Felix felix_prot@hotmail.com

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 ## Not run: # Example 1 ## transforming the data.frame in an object of class geodata data<- as.geodata(soilmoisture) points(data) ## data visualization var<- variog(data, max.dist = 140) ## Obtaining the variogram plot(var) ## Fitting the model mod<- variofit(var,ini.cov.pars = c(2,80),nugget = 2,cov.model = "sph") lines(mod, col=2, lwd=2) ##fitted model ## Bootstrap procedure boot<- gboot_cross(data,var,mod,B=10) ## For better Confidence interval, try B=1000 gboot_CI(boot,digits = 4) ## Bootstrap Confidence Interval gboot_plot(boot) ## Bootstrap Variogram plot # Example 2 ## transforming the data.frame in an object of class geodata data<- as.geodata(NVDI) points(data) ## data visualization var<- variog(data, max.dist = 18) ## Obtaining the variogram plot(var) ## Fitting the model mod<- variofit(var,ini.cov.pars = c(0.003,6),nugget = 0.003,cov.model = "gaus") lines(mod, col=2, lwd=2) ##fitted model ## Bootstrap procedure boot<- gboot_cross(data,var,mod,B=10) ## For better Confidence interval, try B=1000 gboot_CI(boot,digits = 4) ## Bootstrap Confidence Interval gboot_plot(boot) ## Bootstrap Variogram plot ## End(Not run) 

geotoolsR documentation built on March 2, 2020, 5:07 p.m.