| BaseK2BaseC | R Documentation |
Given the coordinates in the Karhunen-Loève expansion base of the Wiener, compute the coordinates in the canonical basis.
BaseK2BaseC(x, nb)
x |
A matrix containing the coordinates in the Karhunen-Loève basis. One observation per column. |
nb |
The dimension of the canonical basis consider. By default,
the dimension is the same as the Karhunen-Loève one
(i.e. number of row of |
The Karhunen-Loève expansion is a sum of an infinity of terms, but here the expansion is truncated to a finite number of terms. Empirically, we remark that using twice the dimension of the canonical basis desired for the number of terms in the expansion is a good compromise.
A object of class fdata with nb discretization points
and the same number of observations as x.
J. Damon
Pumo, B. (1992). Estimation et Prévision de Processus Autoregressifs Fonctionnels. Applications aux Processus à Temps Continu. PhD Thesis, University Paris 6, Pierre et Marie Curie.
simul.wiener, simul.far.wiener
data1 <- BaseK2BaseC(x=matrix(rnorm(50),ncol=5,nrow=10), nb=5)
multplot(data1,whole=TRUE)
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