Abstract
We propose a wavelet based stochastic regression function estimator for the estimation of the regression function for a sequence of mixing stochastic process with a common one-dimensional probability density function. Some asymptotic properties of the proposed estimator are investigated. It is found that the estimators have similar properties to their counterparts studied earlier in literature.
Original language | English |
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Pages (from-to) | 373-385 |
Number of pages | 13 |
Journal | Communications in Statistics - Theory and Methods |
Volume | 37 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2008 |
Externally published | Yes |
Keywords
- Besov space
- mixing stochastic process
- multiresolution analysis
- nonparametric curve estimation
- random design
- wavelets