کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1148590 | 957841 | 2007 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors](/preview/png/1148590.png)
We establish consistency of posterior distribution when a Gaussian process prior is used as a prior distribution for the unknown binary regression function. Specifically, we take the work of Ghosal and Roy [2006. Posterior consistency of Gaussian process prior for nonparametric binary regression. Ann. Statist. 34, 2413–2429] as our starting point, and then weaken their assumptions on the smoothness of the Gaussian process kernel while retaining a stronger yet applicable condition about design points. Furthermore, we extend their results to multi-dimensional covariates under a weaker smoothness condition on the Gaussian process. Finally, we study the extent to which posterior consistency can be achieved under a general model where, when additional hyperparameters in the covariance function of a Gaussian process are involved.
Journal: Journal of Statistical Planning and Inference - Volume 137, Issue 9, 1 September 2007, Pages 2975–2983