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Article: On Nonsmooth Estimating Functions via Jackknife Empirical Likelihood
Title | On Nonsmooth Estimating Functions via Jackknife Empirical Likelihood |
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Authors | |
Keywords | Accelerated failure time model, Bootstrap Jackknife empirical likelihood Perturbation Resampling |
Issue Date | 2016 |
Publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOS |
Citation | Scandinavian Journal of Statistics: theory and applications, 2016, v. 43 n. 1, p. 49-69 How to Cite? |
Abstract | In many applications, the parameters of interest are estimated by solving non-smooth estimating functions with U-statistic structure. Because the asymptotic covariances matrix of the estimator generally involves the underlying density function, resampling methods are often used to bypass the difficulty of non-parametric density estimation. Despite its simplicity, the resultant-covariance matrix estimator depends on the nature of resampling, and the method can be time-consuming when the number of replications is large. Furthermore, the inferences are based on the normal approximation that may not be accurate for practical sample sizes. In this paper, we propose a jackknife empirical likelihood-based inferential procedure for non-smooth estimating functions. Standard chi-square distributions are used to calculate the p-value and to construct confidence intervals. Extensive simulation studies and two real examples are provided to illustrate its practical utilities. |
Persistent Identifier | http://hdl.handle.net/10722/227076 |
ISSN | 2023 Impact Factor: 0.8 2023 SCImago Journal Rankings: 0.892 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Z | - |
dc.contributor.author | Xu, J | - |
dc.contributor.author | Zhou, W | - |
dc.date.accessioned | 2016-07-18T05:31:44Z | - |
dc.date.available | 2016-07-18T05:31:44Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Scandinavian Journal of Statistics: theory and applications, 2016, v. 43 n. 1, p. 49-69 | - |
dc.identifier.issn | 0303-6898 | - |
dc.identifier.uri | http://hdl.handle.net/10722/227076 | - |
dc.description.abstract | In many applications, the parameters of interest are estimated by solving non-smooth estimating functions with U-statistic structure. Because the asymptotic covariances matrix of the estimator generally involves the underlying density function, resampling methods are often used to bypass the difficulty of non-parametric density estimation. Despite its simplicity, the resultant-covariance matrix estimator depends on the nature of resampling, and the method can be time-consuming when the number of replications is large. Furthermore, the inferences are based on the normal approximation that may not be accurate for practical sample sizes. In this paper, we propose a jackknife empirical likelihood-based inferential procedure for non-smooth estimating functions. Standard chi-square distributions are used to calculate the p-value and to construct confidence intervals. Extensive simulation studies and two real examples are provided to illustrate its practical utilities. | - |
dc.language | eng | - |
dc.publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOS | - |
dc.relation.ispartof | Scandinavian Journal of Statistics: theory and applications | - |
dc.rights | The definitive version is available at www.blackwell-synergy.com | - |
dc.subject | Accelerated failure time model, | - |
dc.subject | Bootstrap | - |
dc.subject | Jackknife empirical likelihood | - |
dc.subject | Perturbation | - |
dc.subject | Resampling | - |
dc.title | On Nonsmooth Estimating Functions via Jackknife Empirical Likelihood | - |
dc.type | Article | - |
dc.identifier.email | Xu, J: xujf@hku.hk | - |
dc.identifier.authority | Xu, J=rp02086 | - |
dc.identifier.doi | 10.1111/sjos.12164 | - |
dc.identifier.scopus | eid_2-s2.0-84958159187 | - |
dc.identifier.hkuros | 260470 | - |
dc.identifier.volume | 43 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 49 | - |
dc.identifier.epage | 69 | - |
dc.identifier.isi | WOS:000371237300005 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 0303-6898 | - |