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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