Chaudhuri, Probal ; Dewanji, Anup (1995) On a likelihood-based approach in nonparametric smoothing and cross-validation Statistics & Probability Letters, 22 (1). pp. 7-15. ISSN 0167-7152
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Official URL: http://linkinghub.elsevier.com/retrieve/pii/016771...
Related URL: http://dx.doi.org/10.1016/0167-7152(94)00040-F
Abstract
A likelihood-based generalization of usual kernel and nearest-neighbor-type smoothing techniques and a related extension of the least-squares leave-one-out cross-validation are explored in a generalized regression set up. Several attractive features of the procedure are discussed and asymptotic properties of the resulting nonparametric function estimate are derived under suitable regularity conditions. Large sample performance of likelihood-based leave-one-out cross validation is investigated by means of certain asymptotic expansions.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Elsevier Science. |
| Keywords: | Consistency; Fisher Information; Generalized Regression Model; Maximum Likelihood Cross-validation; Weighted Maximum Likelihood |
| ID Code: | 8133 |
| Deposited On: | 26 Oct 2010 04:17 |
| Last Modified: | 26 Oct 2010 04:17 |
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