## Combining Different Procedures for Adaptive Regression (1998)

Venue: | Journal of Multivariate Analysis |

Citations: | 36 - 7 self |

### BibTeX

@ARTICLE{Yang98combiningdifferent,

author = {Yuhong Yang},

title = {Combining Different Procedures for Adaptive Regression},

journal = {Journal of Multivariate Analysis},

year = {1998},

volume = {74},

pages = {135--161}

}

### Years of Citing Articles

### OpenURL

### Abstract

Given any countable collection of regression procedures (e.g., kernel, spline, wavelet, local polynomial, neural nets, etc), we show that a single adaptive procedure can be constructed to share the advantages of them to a great extent in terms of global squared L 2 risk. The combined procedure basically pays a price only of order 1=n for adaptation over the collection. An interesting consequence is that for a countable collection of classes of regression functions (possibly of completely different characteristics), a minimax-rate adaptive estimator can be constructed such that it automatically converges at the right rate for each of the classes being considered.