smoothing.matrix: Optimal Smoothing Matrix
Description
Optimal Smoothing Matrix
Usage
smoothing.matrix(R, startup_period = 10, training_period = 60, seed = 9999, trials = 50, method = "L-BFGS-B", lambda = 0.2)
Arguments
startup_period
length of samples required to calculate initial values
training_period
length of samples required to calculate forecast errors
for evalualating the objective
seed
random seed to replicate the starting values for optimization
trials
number of strarting values to try for any optimization.
Large number of trials for high dimensions can be time consuming
method
optimization method to use to evaluate an estimate of
smoothing matrix. Default is L-BFGS-B
lambda
known constant as described in the paper. Defaulted to 0.2
Details
Calcuation of smoothing matrix is done by assuming that the smoothing matrix
is symmetrix and has a spectral decomposition. The orthogonal matrix in the
decomposition is calculated using the product of givens rotation matrices and
requires d(d-1)/2 angles for a d dimensional matrix. The eigenvalues are
restricted to lie in [0,1].