Name
Title | ||
|---|---|---|
A consistent deterministic regression tree for non-parametric prediction of time series. |
Abstract | ||
|---|---|---|
We study online prediction of bounded stationary ergodic processes. To do so, we consider the setting of prediction of individual sequences and build a deterministic regression tree that performs asymptotically as well as the best L-Lipschitz constant predictors. Then, we show why the obtained regret bound entails the asymptotical optimality with respect to the class of bounded stationary ergodic processes. |
Year | Venue | Field |
|---|---|---|
2014 | CoRR | Decision tree,Stationary ergodic process,Regret,Ergodic theory,Nonparametric statistics,Statistics,Mathematics,Bounded function |
DocType | Volume | Citations |
Journal | abs/1405.1533 | 1 |
PageRank | References | Authors |
0.41 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pierre Gaillard | 1 | 79 | 10.89 |
| Paul Baudin | 2 | 1 | 0.41 |