# gboot_block: Block bootstrap In geotoolsR: Tools to Improve the Use of Geostatistic

## Description

Performs a bootstrap based on subdivision of data in blocks

## Usage

 1 gboot_block(data,var,model,B,L1,L2) 

## 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). L1 number of cuts in the vertical (L1xL2 blocks). L2 number of cuts in the horizontal (L1xL2 blocks).

## Details

The algorithm for the block bootstrap is an adaptation of the time series bootstrap. Consider that your data presents the second order stationarity, so, we can subdivide them into small blocks. The steps of the algorithm are:

1. Subdivide the data into L1xL2 blocks;

2. Realocate each block with probability\frac{1}{L1L2} ;

3. Calculate the new variogram from the new data;

4. Calculate and save the statistics of interest;

5. Return to step 2 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

## References

DAVISON, A.C.; HINKLEY, D. V. Bootstrap Methods and their Application. [s.l.] Cambridge University Press, 1997. p. 582

## 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_block(data,var,mod,B=10, L1=2, L2=2) ## 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<- boot<- gboot_block(data,var,mod,B=10, L1=2, L2=2) ## 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.