Description Usage Arguments Details Value Author(s) References See Also Examples
This function is the "engine" of the TRMF package. It takes a previously created TRMF object and fits it to the data using an alternating least squares algorithm.
A TRMF object to be fit.
Number of alternating least squares iterations
If a coefficient model is not present in
object, it adds a L2 regularization model. If no time series models have been added to
object, it adds a simple model using
train returns a fitted object of
TRMF" that contains the data, all added models, matrix factorization and fitted model. The matrix factors Xm, Fm
are stored in
object$Factors$Fm respectively. Use
fitted to get fitted model, use
resid to get residuals, use
coef to get coefficients (Fm matrix) and
components to get
Yu, Hsiang-Fu, Nikhil Rao, and Inderjit S. Dhillon. "High-dimensional time series prediction with missing values." arXiv preprint arXiv:1509.08333 (2015).
1 2 3 4 5 6 7 8 9
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.