gfd_clasif_data: Divide the data in train and test dataset

In SpatFD: Functional Geostatistics: Univariate and Multivariate Functional Spatial Prediction

Divide the data in train and test dataset

Description

This function divides the data in train and test datasets

Usage

  gfd_clasif_data(gfd_data, prop.train, seed = NULL) 

Arguments

gfd_data	Object of class 'gfdata'. Not NULL.
prop.train	Number between 0 and 1, indicating the proportion to be left on train dataset
seed	seed for the sampling algorithms

Value

gfdata divided object

Author(s)

Diego Sandoval [e-mail].

References

Bohorquez, M., Giraldo, R., & Mateu, J. (2016). Multivariate functional random fields: prediction and optimal sampling. Stochastic Environmental Research and Risk Assessment, 31, pages53–70 (2017).

Examples

  library(SpatFD)
  data(vowels)
  
  #### Create parameters and names for the data.
  p = 228 ; nelec = 21 ; nvow = 5
  names_vowels = c("a","e","i","o","u")
  n.basis<-c(14,13,12,13,11)
  
  s4.gfdata = gfdata(data=vowels,p=p,names=names_vowels,coords=vowels_coords,nbasis=n.basis)
  s4.sep=gfd_clasif_data(s4.gfdata, 0.8,seed = 2910)
  
  s4.train=s4.sep$train
  s4.test=s4.sep$test
  

SpatFD documentation built on June 22, 2024, 10:41 a.m.