warp: Evaluates a composition of warplets.
In MRwarping: Multiresolution time warping for functional data.

Description Usage Arguments Value Author(s) References Examples

The function warp evaluates a composition of warplets that are constructed by the function comp.

1	warp(A, Lambda, R1, R2, x)

`A`	Vector of centers of the warplets.
`Lambda`	Vector of intensities.
`R1`	Vector of radii on the left-hand side of the centers.
`R2`	Vector of radii on the right-hand side of the centers.
`x`	Vector of time points at which to evaluate the warping function.

warp contains the warping function evaluated at x, see also comp.

L. Slaets, G. Claeskens, B.W. Silverman.

See the papers: Slaets, Claeskens and Silverman (2010). Warping functional data in R and C via a Bayesian Multiresolution approach. Journal of Statistical Software, 55(3), 1-22,
URL http://www.jstatsoft.org/v55/i03/.

Claeskens, Silverman and Slaets (2010). A multiresolution approach to time warping achievec by a Bayesian prior-posterior transfer fitting strategy. Journal of the Royal Statistical Society, Series B, 72(5), 673-694.

t = seq(0,10,length.out=1000)
tau.t = warp(c(5,2),c(0.6,0.4),c(2,1.5),c(3,2),t)

## The function is currently defined as
warp =
function(A,Lambda,R1,R2,x)
{
Wx = x
for (i in 1:length(A))
    	{
	warp = comp(A[i],Lambda[i],R1[i],R2[i],Wx)
	Wx = warp
	}
return(Wx)
}