gfdata {SpatFD}

Creates gfdata objects.

Description

Creates an object of the class gfdata from spatial coordinates, and functions or time-series observed at each spatial location. Time series is a generic term. In fact, observations might be across the frequency or across another spatial dimension such as depth, instead of time.

Usage

  gfdata(data, p, basis = "Bsplines", coords = NULL, nbasis = NULL, 
                      names = NULL, lambda = 0)

Arguments

data

Data must be provided in a matrix where each column corresponds to a subject, and the rows are a sequence of data points, that is, the rows are ordered according to time, frequency, depth, …. Also must include a column with classes for classification in the last column

p

Number of repetitions for each class

basis

Basis functions. "Fourier" or "Bsplines". By default, "Bsplines".

coords

A matrix with spatial coordinates (x,y).

nbasis

The number of basis functions.

names

Names for the data classes.

lambda

The value of the smoothing parameter.

Details

The gfdata-objects storage the functional data, its parameters, the functional principal component analysis results, and the spatial coordinates for each variable. Each variable has its own functional data, data-frame or matrix and its spatial coordinates file.

Value

For each subject and class: The functional data and functional principal components linked with spatial coordinates.

Author(s)

Venus Puertas [e-mail].

References

Bohorquez, M., Giraldo, R., & Mateu, J. (2016). Optimal sampling for spatial prediction of functional data. Statistical Methods & Applications, 25(1), 39-54.

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).

See Also

summary.gfdata

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)