Description Usage Arguments Value Author(s) References Examples
This function allows you to fit discrete functional data (fdframe) as functions in RKHS solving a regularization problem as stated in Munoz (2010).
1 2 |
fdframe |
functional data |
gamma |
regularization parameter. |
kerfunc |
kernel function rbf or poly to be used. |
kerpar |
a list of kernel parameters where sigma is the scale with both kernels. |
fdframe |
raw data in an fdframe object. |
f |
estimated functional data |
alpha |
coefficients for the linear combination. |
lambda.star |
reduced coefficients for the linear combination. |
Hernandez and Martos
Munoz A. et al (2010). Representing functional data using support vector machines. Pattern recognition letters, 31(6).
1 2 3 4 5 6 7 8 9 10 | data(merval); t <- as.Date(merval[1:100,1])
t <- as.numeric(( t - min(t) ) / 154)
raw.data <-fdframe(t = t, Y = merval[1:100,2:5])
plot(raw.data, xlab='time', ylab='Merval raw data')
f.data <- rkhs(raw.data, gamma = 0.001, kerpar = list(sigma = 8))
print(f.data)
plot(f.data, xlab='time', ylab='Merval data')
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