Description Usage Arguments Value
This function create a RKHS smoothing mean from an existing data set with known eigenvalues and eigenvectors
1 | g.X.RKHS(N, n, e.val.x, e.vec.x, tau, phi, mu, m, e.val.z)
|
N |
real number, number of observations |
n |
real number, number of grid points |
e.val.x |
real vector n*1, eigenvalues |
e.vec.x |
real valued matrix n*N, eigenvectors |
tau |
range of the uniform distribution in KL expansion |
phi |
real number, penalty parameter |
mu |
real vector n*1, initial mean vector |
m |
positive integer, number of eigenvectors are going to be used |
e.val.z |
real valued matrix n*N, eigenvectors of noise |
a real valued matrix n*N
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