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Asymptotic Properties of Just-In-Time Models

1997; Elsevier BV; Volume: 30; Issue: 11 Linguagem: Inglês

10.1016/s1474-6670(17)43004-7

2589-3653

Anders Stenman, Alexander Nazin, Fredrik Gustafsson,

Fault Detection and Control Systems

The concept of Just-in-Time models has been introduced for models that are not estimated until they are really needed. The prediction is taken as a weighted average of neighboring points in the regressor space, such that an optimal bias/variance trade-off is achieved. The asymptotic properties of the method are investigated, and are compared to the corresponding properties of related statistical non-parametric kernel methods. It is shown that the rate of convergence for Just-in-Time models at least is in the same order as traditional kernel estimators, and that better rates probably can be achieved.