Fuzzy statistics: hypothesis testing

Fuzzy statistics: hypothesis testing

Our method of estimation of parameters in statistics uses a set of confidence intervals producing a triangular shaped fuzzy number for the estimator. Using this fuzzy estimator in hypothesis testing produces a fuzzy test statistic and fuzzy critical values in fuzzy hypothesis testing. We show how th...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Soft computing (Berlin, Germany) Germany), 2005-07, Vol.9 (7), p.512-518
1. Verfasser: Buckley, James J.
Format: Artikel
Sprache:eng
Schlagworte:
Confidence intervals
Fuzzy sets
Fuzzy systems
Null hypothesis
Statistical analysis
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 518
container_issue 7
container_start_page 512
container_title Soft computing (Berlin, Germany)
container_volume 9
creator Buckley, James J.
description Our method of estimation of parameters in statistics uses a set of confidence intervals producing a triangular shaped fuzzy number for the estimator. Using this fuzzy estimator in hypothesis testing produces a fuzzy test statistic and fuzzy critical values in fuzzy hypothesis testing. We show how these fuzzy sets may be used to derive the usual conclusion of: (1) reject the null hypothesis, or (2) do not reject the null hypothesis.
doi_str_mv 10.1007/s00500-004-0368-5
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2917902039</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2917902039</sourcerecordid><originalsourceid>FETCH-LOGICAL-c273t-b788b1d94a2f4c9b782365bf0e978d06ce67aeff8f30b340d68598e446f39e053</originalsourceid><addsrcrecordid>eNotkEtPwzAQhC0EEqXwA7hFgqth7fWTG6ooIFXiAmcrD5umgibYziH99aSE0-yMRjvSR8g1gzsGoO8TgASgAIICKkPlCVkwgUi10Pb07-ZUK4Hn5CKlHQBnWuKC3K6Hw2EsUi5zm3Jbp4diO_Zd3vrUpiL7Kdt_XpKzUH4lf_WvS_KxfnpfvdDN2_Pr6nFDa64x00obU7HGipIHUdvJclSyCuCtNg2o2itd-hBMQKhQQKOMtMYLoQJaDxKX5Gb-28fuZ5i23a4b4n6adNwybYED2qnF5lYdu5SiD66P7XcZR8fAHWG4GYabYLgjDCfxF1sdULo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2917902039</pqid></control><display><type>article</type><title>Fuzzy statistics: hypothesis testing</title><source>Springer Nature - Complete Springer Journals</source><source>ProQuest Central</source><creator>Buckley, James J.</creator><creatorcontrib>Buckley, James J.</creatorcontrib><description>Our method of estimation of parameters in statistics uses a set of confidence intervals producing a triangular shaped fuzzy number for the estimator. Using this fuzzy estimator in hypothesis testing produces a fuzzy test statistic and fuzzy critical values in fuzzy hypothesis testing. We show how these fuzzy sets may be used to derive the usual conclusion of: (1) reject the null hypothesis, or (2) do not reject the null hypothesis.</description><identifier>ISSN: 1432-7643</identifier><identifier>EISSN: 1433-7479</identifier><identifier>DOI: 10.1007/s00500-004-0368-5</identifier><language>eng</language><publisher>Heidelberg: Springer Nature B.V</publisher><subject>Confidence intervals ; Fuzzy sets ; Fuzzy systems ; Null hypothesis ; Statistical analysis</subject><ispartof>Soft computing (Berlin, Germany), 2005-07, Vol.9 (7), p.512-518</ispartof><rights>Springer-Verlag Berlin Heidelberg 2004.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c273t-b788b1d94a2f4c9b782365bf0e978d06ce67aeff8f30b340d68598e446f39e053</citedby><cites>FETCH-LOGICAL-c273t-b788b1d94a2f4c9b782365bf0e978d06ce67aeff8f30b340d68598e446f39e053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2917902039?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,43781</link.rule.ids></links><search><creatorcontrib>Buckley, James J.</creatorcontrib><title>Fuzzy statistics: hypothesis testing</title><title>Soft computing (Berlin, Germany)</title><description>Our method of estimation of parameters in statistics uses a set of confidence intervals producing a triangular shaped fuzzy number for the estimator. Using this fuzzy estimator in hypothesis testing produces a fuzzy test statistic and fuzzy critical values in fuzzy hypothesis testing. We show how these fuzzy sets may be used to derive the usual conclusion of: (1) reject the null hypothesis, or (2) do not reject the null hypothesis.</description><subject>Confidence intervals</subject><subject>Fuzzy sets</subject><subject>Fuzzy systems</subject><subject>Null hypothesis</subject><subject>Statistical analysis</subject><issn>1432-7643</issn><issn>1433-7479</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNotkEtPwzAQhC0EEqXwA7hFgqth7fWTG6ooIFXiAmcrD5umgibYziH99aSE0-yMRjvSR8g1gzsGoO8TgASgAIICKkPlCVkwgUi10Pb07-ZUK4Hn5CKlHQBnWuKC3K6Hw2EsUi5zm3Jbp4diO_Zd3vrUpiL7Kdt_XpKzUH4lf_WvS_KxfnpfvdDN2_Pr6nFDa64x00obU7HGipIHUdvJclSyCuCtNg2o2itd-hBMQKhQQKOMtMYLoQJaDxKX5Gb-28fuZ5i23a4b4n6adNwybYED2qnF5lYdu5SiD66P7XcZR8fAHWG4GYabYLgjDCfxF1sdULo</recordid><startdate>200507</startdate><enddate>200507</enddate><creator>Buckley, James J.</creator><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>200507</creationdate><title>Fuzzy statistics: hypothesis testing</title><author>Buckley, James J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c273t-b788b1d94a2f4c9b782365bf0e978d06ce67aeff8f30b340d68598e446f39e053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Confidence intervals</topic><topic>Fuzzy sets</topic><topic>Fuzzy systems</topic><topic>Null hypothesis</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Buckley, James J.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Soft computing (Berlin, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Buckley, James J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy statistics: hypothesis testing</atitle><jtitle>Soft computing (Berlin, Germany)</jtitle><date>2005-07</date><risdate>2005</risdate><volume>9</volume><issue>7</issue><spage>512</spage><epage>518</epage><pages>512-518</pages><issn>1432-7643</issn><eissn>1433-7479</eissn><abstract>Our method of estimation of parameters in statistics uses a set of confidence intervals producing a triangular shaped fuzzy number for the estimator. Using this fuzzy estimator in hypothesis testing produces a fuzzy test statistic and fuzzy critical values in fuzzy hypothesis testing. We show how these fuzzy sets may be used to derive the usual conclusion of: (1) reject the null hypothesis, or (2) do not reject the null hypothesis.</abstract><cop>Heidelberg</cop><pub>Springer Nature B.V</pub><doi>10.1007/s00500-004-0368-5</doi><tpages>7</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1432-7643
ispartof Soft computing (Berlin, Germany), 2005-07, Vol.9 (7), p.512-518
issn 1432-7643
1433-7479
language eng
recordid cdi_proquest_journals_2917902039
source Springer Nature - Complete Springer Journals; ProQuest Central
subjects Confidence intervals
Fuzzy sets
Fuzzy systems
Null hypothesis
Statistical analysis
title Fuzzy statistics: hypothesis testing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-01T17%3A51%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fuzzy%20statistics:%20hypothesis%20testing&rft.jtitle=Soft%20computing%20(Berlin,%20Germany)&rft.au=Buckley,%20James%20J.&rft.date=2005-07&rft.volume=9&rft.issue=7&rft.spage=512&rft.epage=518&rft.pages=512-518&rft.issn=1432-7643&rft.eissn=1433-7479&rft_id=info:doi/10.1007/s00500-004-0368-5&rft_dat=%3Cproquest_cross%3E2917902039%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2917902039&rft_id=info:pmid/&rfr_iscdi=true