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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭明燕(Ming-Yen Cheng) | |
| dc.contributor.author | Lu-Hung Chen | en |
| dc.contributor.author | 陳律閎 | zh_TW |
| dc.date.accessioned | 2021-05-20T19:59:46Z | - |
| dc.date.available | 2010-03-10 | |
| dc.date.available | 2021-05-20T19:59:46Z | - |
| dc.date.copyright | 2010-03-10 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-02-22 | |
| dc.identifier.citation | Aerts, M., and Claeskens, G. (1997), “Local polynomial estimators in multiparameter likelihood models,” Journal of the American Statistical Association, 92, 1536-1545.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8688 | - |
| dc.description.abstract | Multiparameter likelihood models (MLMs) with multiple covariates have a
wide range of applications; however, they encounter the “curse of dimension- ality” problem when the dimension of the covariates is large. We develop a generalized multiparameter likelihood model that copes with multiple covari- ates and adapts to dynamic structural changes well. It includes some popular models, such as the partially linear and varying-coefficients models, as special cases. We discuss the backfitting and profile likelihood procedures and present a simple, effective two-step method to estimate both the parametric and the nonparametric components when the model is fixed. All these estimators of the parametric component has the n−1/2 convergence rate, and the estimator of the nonparametric component enjoys an adaptivity property. We suggest a data-driven procedure for selecting the bandwidths, and propose an initial estimator in backfitting and profile likelihood estimation of the parametric part to ensure stability of the approach in general settings. We further develop an automatic procedure to identify constant parameters in the underlying model. We provide several simulation studies and an application to infant mortality data of China to demonstrate the performance of our proposed method. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T19:59:46Z (GMT). No. of bitstreams: 1 ntu-99-D95221006-1.pdf: 788411 bytes, checksum: e61bc5de732dda8258fe40ac3dc528f0 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | ABSTRACT i
中文摘要 ii 致謝 iii 1 Introduction 1 2 Motivating examples and model identifiability 7 3 Reviews of related models 11 4 Estimation procedures 16 4.1 Backfitting estimation . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.2 Profile likelihood estimation . . . . . . . . . . . . . . . . . . . . . . . 18 4.3 Two-step estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5 Bandwidth selection and identifying constant parameters 26 5.1 Model selection criteria . . . . . . . . . . . . . . . . . . . . . . . . . . 27 5.1.1 Akaike Information Criterion (AIC) . . . . . . . . . . . . . . 27 5.1.2 Bayesian Information Criterion (BIC) . . . . . . . . . . . . . 29 5.2 Bandwidth selection . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 5.3 Identifying constant parameters . . . . . . . . . . . . . . . . . . . . . 32 6 Asymptotic properties 36 7 Simulation study and data analysis 40 7.1 Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 7.2 Weibull model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 7.3 Hazard Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 8 Analysis for infant mortality in China 63 9 Conclusion and Future Works 77 REFERENCES 79 A Proofs for Backfitting 83 B Proofs for Profile Likelihood Estimation 90 C Proofs for 2-Step Estimation 94 | |
| dc.language.iso | en | |
| dc.title | 廣義多參數概似模型之估計 | zh_TW |
| dc.title | On Estimation Methods in Generalized Multiparameter Likelihood Model | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 曾勝滄(Sheng-Tsaing Tseng),戴政(John Jen Tai),張淑惠(Shu Hui Chang),丘政民(Jeng-Min Chiou) | |
| dc.subject.keyword | 帶寬選取,模型選取,半參數模型,變係數模型, | zh_TW |
| dc.subject.keyword | Bandwidth selection,Model selection,Multiple covariate,Partially linear model,Backfitting,Profi,le likelihood,Varying-coeffi,cient model,Semiparametric models, | en |
| dc.relation.page | 101 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2010-02-22 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 數學研究所 | zh_TW |
| 顯示於系所單位： | 數學系 | |
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