gboot_cloud: Bootstrap of the variogram cloud

In geotoolsR: Tools to Improve the Use of Geostatistic

Description

Performs a boostrap based on the variogram cloud

Usage

gboot_cloud(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

The variogram cloud is computed by the function variog. It provides all the possible pairs that will generate the classical variogram. The algorithm performs a classical bootstrap in each lag of the variogram. The steps are:

1. Calculate the variogram cloud;

2. Obtain the number of lags (See details in variog: defining the bins);

3. Sample with replacement in each lag;

4. Create a new variogram using the average of all pairs in each lag;

5. Calculate and save the statistics of interest;

6. Return to step 3 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 [e-mail]

Vinicius Basseto Felix [e-mail]

Examples

## 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_cloud(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_cloud(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.