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Bayesian Methods for Wavelet Series in Single-Index Models
| Content Provider | Scilit |
|---|---|
| Author | Park, Chun Gun Vannucci, Marina Hart, Jeffrey D. |
| Copyright Year | 2005 |
| Description | Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. This article proposes a nonparametric estimation approach that combines wavelet methods for nonequispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods. |
| Related Links | http://www.stat.rice.edu/~marina/papers/jcgs05.pdf |
| Ending Page | 794 |
| Page Count | 25 |
| Starting Page | 770 |
| ISSN | 10618600 |
| e-ISSN | 15372715 |
| DOI | 10.1198/106186005x79007 |
| Journal | Journal of Computational and Graphical Statistics |
| Issue Number | 4 |
| Volume Number | 14 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2005-12-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Journal of Computational and Graphical Statistics Statistics and Probability Function Models Single Index Prior Bayesian Coefficients Wavelet Methods Index Models |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Discrete Mathematics and Combinatorics Statistics, Probability and Uncertainty |
