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Create a Process via Karhunen-Loeve Representation
kl.process( domain = c(0, 1), eigen.values = 1/(2^(1:25)), eigen.functions = c("FOURIER", "COS", "SIN", "LEGENDRE"), distribution = c("GAUSSIAN", "LAPLACE", "EXPONENTIAL", "GAMMA"), corr = NULL )
domain of the process.
vector of eigenvalues in the K-L expansion.
string that specifies the eigenfunctions in the K-L expansion.
string specifying the distribution of FPC scores.
correlation matrix optionally specifying correlation among the random coefficients; default: NULL.
a function hanlde in the form of X(tObs,n) which generates n independent trajectories observed at tObs.
X(tObs,n)
n
tObs
# NOT RUN { X <- kl.process() X(regular.grid(50),25) # }
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