| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1149520 | Journal of Statistical Planning and Inference | 2010 | 8 Pages |
Abstract
Given m time series regression models, linear or not, with additive noise components, it is shown how to estimate semiparametrically the predictive probability distribution of one of the time series conditional on past random covariate data. This is done by assuming that the distributions of the residual components associated with the regression models are tilted versions of a reference distribution.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Benjamin Kedem, Richard E. Gagnon,