Abstract
This note considers the kernel estimation of a linear random field on Z 2. Instead of imposing certain mixing conditions on the random fields, it is assumed that the weights of the innovations satisfy a summability property. By building a martingale decomposition based on a suitable filtration, asymptotic normality is proven for the kernel estimator of the marginal density of the random field.
Original language | English |
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Pages (from-to) | 267-286 |
Number of pages | 20 |
Journal | Journal of Theoretical Probability |
Volume | 21 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2008 Jun 1 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Mathematics(all)
- Statistics, Probability and Uncertainty