Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction
This paper addresses the problem of estimating the extreme value index in presence of random censoring for distributions in the Weibull domain of attraction. The methodologies introduced in [Worms (2014)], in the heavy-tailed case, are adapted here to the negative extreme value index framework, lead...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Worms, Julien Worms, Rym |
| description | This paper addresses the problem of estimating the extreme value index in
presence of random censoring for distributions in the Weibull domain of
attraction. The methodologies introduced in [Worms (2014)], in the heavy-tailed
case, are adapted here to the negative extreme value index framework, leading
to the definition of weighted versions of the popular moments of relative
excesses with arbitrary exponent. This leads to the definition of two families
of estimators (with an adaptation of the so called Moment estimator as a
particular case), for which the consistency is proved under a first order
condition. Illustration of their performance, issued from an extensive
simulation study, are provided. |
| doi_str_mv | 10.48550/arxiv.1506.03765 |
| format | Article |
| fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_1506_03765</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1506_03765</sourcerecordid><originalsourceid>FETCH-LOGICAL-a675-268098d8ecc4955dec7de7bdc72a44b683f80e868d744bcb54551a4015bb9d913</originalsourceid><addsrcrecordid>eNotj81OwzAQhH3hgAoPwAm_QILTeG3niCr-pKJeKnGM1vZGRCQxctwqfXtM4DSa0cxIH2N3lSilARAPGJf-XFYgVClqreCafb2HkabEaU79iCnEmYeOp0_itKRII_EzDifi_eRp4V2IPOLkwzhcuKNpDpE895gwF9bVB_X2NAw8VzBH-QtTiuhSH6YbdtXhMNPtv27Y8fnpuHst9oeXt93jvkClodgqIxrjDTknGwBPTnvS1ju9RSmtMnVnBBllvM7WWZAAFUpRgbWNb6p6w-7_blfa9jtmsHhpf6nblbr-AXAsVBw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction</title><source>arXiv.org</source><creator>Worms, Julien ; Worms, Rym</creator><creatorcontrib>Worms, Julien ; Worms, Rym</creatorcontrib><description>This paper addresses the problem of estimating the extreme value index in
presence of random censoring for distributions in the Weibull domain of
attraction. The methodologies introduced in [Worms (2014)], in the heavy-tailed
case, are adapted here to the negative extreme value index framework, leading
to the definition of weighted versions of the popular moments of relative
excesses with arbitrary exponent. This leads to the definition of two families
of estimators (with an adaptation of the so called Moment estimator as a
particular case), for which the consistency is proved under a first order
condition. Illustration of their performance, issued from an extensive
simulation study, are provided.</description><identifier>DOI: 10.48550/arxiv.1506.03765</identifier><language>eng</language><subject>Mathematics - Statistics Theory ; Statistics - Theory</subject><creationdate>2015-06</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1506.03765$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1506.03765$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Worms, Julien</creatorcontrib><creatorcontrib>Worms, Rym</creatorcontrib><title>Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction</title><description>This paper addresses the problem of estimating the extreme value index in
presence of random censoring for distributions in the Weibull domain of
attraction. The methodologies introduced in [Worms (2014)], in the heavy-tailed
case, are adapted here to the negative extreme value index framework, leading
to the definition of weighted versions of the popular moments of relative
excesses with arbitrary exponent. This leads to the definition of two families
of estimators (with an adaptation of the so called Moment estimator as a
particular case), for which the consistency is proved under a first order
condition. Illustration of their performance, issued from an extensive
simulation study, are provided.</description><subject>Mathematics - Statistics Theory</subject><subject>Statistics - Theory</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj81OwzAQhH3hgAoPwAm_QILTeG3niCr-pKJeKnGM1vZGRCQxctwqfXtM4DSa0cxIH2N3lSilARAPGJf-XFYgVClqreCafb2HkabEaU79iCnEmYeOp0_itKRII_EzDifi_eRp4V2IPOLkwzhcuKNpDpE895gwF9bVB_X2NAw8VzBH-QtTiuhSH6YbdtXhMNPtv27Y8fnpuHst9oeXt93jvkClodgqIxrjDTknGwBPTnvS1ju9RSmtMnVnBBllvM7WWZAAFUpRgbWNb6p6w-7_blfa9jtmsHhpf6nblbr-AXAsVBw</recordid><startdate>20150611</startdate><enddate>20150611</enddate><creator>Worms, Julien</creator><creator>Worms, Rym</creator><scope>AKZ</scope><scope>EPD</scope><scope>GOX</scope></search><sort><creationdate>20150611</creationdate><title>Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction</title><author>Worms, Julien ; Worms, Rym</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a675-268098d8ecc4955dec7de7bdc72a44b683f80e868d744bcb54551a4015bb9d913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Mathematics - Statistics Theory</topic><topic>Statistics - Theory</topic><toplevel>online_resources</toplevel><creatorcontrib>Worms, Julien</creatorcontrib><creatorcontrib>Worms, Rym</creatorcontrib><collection>arXiv Mathematics</collection><collection>arXiv Statistics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Worms, Julien</au><au>Worms, Rym</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction</atitle><date>2015-06-11</date><risdate>2015</risdate><abstract>This paper addresses the problem of estimating the extreme value index in
presence of random censoring for distributions in the Weibull domain of
attraction. The methodologies introduced in [Worms (2014)], in the heavy-tailed
case, are adapted here to the negative extreme value index framework, leading
to the definition of weighted versions of the popular moments of relative
excesses with arbitrary exponent. This leads to the definition of two families
of estimators (with an adaptation of the so called Moment estimator as a
particular case), for which the consistency is proved under a first order
condition. Illustration of their performance, issued from an extensive
simulation study, are provided.</abstract><doi>10.48550/arxiv.1506.03765</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.48550/arxiv.1506.03765 |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_arxiv_primary_1506_03765 |
| source | arXiv.org |
| subjects | Mathematics - Statistics Theory Statistics - Theory |
| title | Moment estimators of the extreme value index for randomly censored data in the Weibull domain of attraction |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T18%3A28%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Moment%20estimators%20of%20the%20extreme%20value%20index%20for%20randomly%20censored%20data%20in%20the%20Weibull%20domain%20of%20attraction&rft.au=Worms,%20Julien&rft.date=2015-06-11&rft_id=info:doi/10.48550/arxiv.1506.03765&rft_dat=%3Carxiv_GOX%3E1506_03765%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |