Authors: Stephen P. Smith
A second order time series model is described, and generalized to the multivariate situation. The model is highly flexible, and is suitable for non-parametric regression, coming with unequal time steps. The resulting K-matrix is described, leading to its possible factorization and differentiation using general purpose software that was recently developed. This makes it possible to estimate variance matrices in the multivariate model corresponding the signal and noise components of the model, by restricted maximum likelihood. A nested iteration algorithm is presented for conducting the maximization, and an illustration of the methods are demonstrated on a 4-variate time series with 89 observations.
Comments: 15 Pages.
[v1] 2019-01-06 15:23:31 (removed)
[v2] 2019-01-08 22:24:19
Unique-IP document downloads: 16 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.