derivcurves: Computes the derivative of functional data.

In MFHD: Multivariate Functional Halfspace Depth

Description

Often one set of curves y1 is given, and the second set of curves y2 are the (estimated) derivatives. This function computes these derivatives.

Usage

  derivcurves(y1,method="bspline")

Arguments

y1	A n by T matrix of functional data.
method	Type of derivative method, for more information see details.

Details

• If method="bspline", "exponential", "fourier", "monomial" or "polynomial", the "derivcurves" function creates a basis to represent the functional data.

• If "method"="diff", raw derivation is applied. Not recommended to use this method when the values are not equally spaced.

This function is a wraper for "fda.usc::fdata.deriv". See help("fda.usc::fdata.deriv").

Value

Returns the derivative of functional data.

Author(s)

K. Vakili.

Examples

set.seed(123)	
n<-50;
T<-100;	 
t.<-seq(0,2*pi,l=T)
y<-matrix(NA,n,T)
for(i in 1:n)	y[i,]<-runif(1,0,1)*sin(t.)+runif(1,0,1)*cos(t.)
y2<-derivcurves(y)	

MFHD documentation built on May 2, 2019, 3:24 a.m.