File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1007/BF02509236
- Scopus: eid_2-s2.0-29344455142
- WOS: WOS:000232494500005
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Profile empirical likelihood for parametric and semiparametric models
Title | Profile empirical likelihood for parametric and semiparametric models |
---|---|
Authors | |
Keywords | Efficiency Empirical Likelihood Parametric And Semiparametric Models Profile Likelihood |
Issue Date | 2005 |
Citation | Annals Of The Institute Of Statistical Mathematics, 2005, v. 57 n. 3, p. 485-505 How to Cite? |
Abstract | This paper introduces a profile empirical likelihood and a profile conditionally empirical likelihood to estimate the parameter of interest in the presence of nuisance parameters respectively for the parametric and semiparametric models. It is proven that these methods propose some efficient estimators of parameters of interest in the sense of least-favorable efficiency. Particularly, for the decomposable semiparametric models, an explicit representation for the estimator of parameter of interest is derived from the proposed nonparametric method. These new estimations are different from and more efficient than the existing estimations. Some examples and simulation studies are given to illustrate the theoretical results. © 2005 The Institute of Statistical Mathematics. |
Persistent Identifier | http://hdl.handle.net/10722/172418 |
ISSN | 2021 Impact Factor: 1.180 2020 SCImago Journal Rankings: 0.650 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lin, L | en_US |
dc.contributor.author | Zhu, L | en_US |
dc.contributor.author | Yuen, KC | en_US |
dc.date.accessioned | 2012-10-30T06:22:24Z | - |
dc.date.available | 2012-10-30T06:22:24Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.citation | Annals Of The Institute Of Statistical Mathematics, 2005, v. 57 n. 3, p. 485-505 | en_US |
dc.identifier.issn | 0020-3157 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/172418 | - |
dc.description.abstract | This paper introduces a profile empirical likelihood and a profile conditionally empirical likelihood to estimate the parameter of interest in the presence of nuisance parameters respectively for the parametric and semiparametric models. It is proven that these methods propose some efficient estimators of parameters of interest in the sense of least-favorable efficiency. Particularly, for the decomposable semiparametric models, an explicit representation for the estimator of parameter of interest is derived from the proposed nonparametric method. These new estimations are different from and more efficient than the existing estimations. Some examples and simulation studies are given to illustrate the theoretical results. © 2005 The Institute of Statistical Mathematics. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Annals of the Institute of Statistical Mathematics | en_US |
dc.subject | Efficiency | en_US |
dc.subject | Empirical Likelihood | en_US |
dc.subject | Parametric And Semiparametric Models | en_US |
dc.subject | Profile Likelihood | en_US |
dc.title | Profile empirical likelihood for parametric and semiparametric models | en_US |
dc.type | Article | en_US |
dc.identifier.email | Yuen, KC: kcyuen@hku.hk | en_US |
dc.identifier.authority | Yuen, KC=rp00836 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1007/BF02509236 | en_US |
dc.identifier.scopus | eid_2-s2.0-29344455142 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-29344455142&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 57 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.spage | 485 | en_US |
dc.identifier.epage | 505 | en_US |
dc.identifier.isi | WOS:000232494500005 | - |
dc.publisher.place | Germany | en_US |
dc.identifier.scopusauthorid | Lin, L=35315971600 | en_US |
dc.identifier.scopusauthorid | Zhu, L=7404201068 | en_US |
dc.identifier.scopusauthorid | Yuen, KC=7202333703 | en_US |
dc.identifier.issnl | 0020-3157 | - |