{"id":"https://openalex.org/W7105531163","doi":"https://doi.org/10.71602/tfss.2026.1200900","title":"Fuzzy Bayesian, E-Bayesian, and Hierarchical Bayesian Estimations of R = P(X&gt;Y ) in Weibull Distribution under Type II censored Data","display_name":"Fuzzy Bayesian, E-Bayesian, and Hierarchical Bayesian Estimations of R = P(X&gt;Y ) in Weibull Distribution under Type II censored Data","publication_year":2025,"publication_date":"2025-03-04","ids":{"openalex":"https://openalex.org/W7105531163","doi":"https://doi.org/10.71602/tfss.2026.1200900"},"language":"en","primary_location":{"id":"doi:10.71602/tfss.2026.1200900","is_oa":true,"landing_page_url":"https://doi.org/10.71602/tfss.2026.1200900","pdf_url":null,"source":{"id":"https://openalex.org/S169411308","display_name":"Fuzzy Sets and Systems","issn_l":"0165-0114","issn":["0165-0114","1872-6801"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.71602/tfss.2026.1200900","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fayyaz Heydari, Kazem","orcid":"https://orcid.org/0000-0001-7928-3741"},"institutions":[{"id":"https://openalex.org/I55547365","display_name":"Payame Noor University","ror":"https://ror.org/031699d98","country_code":"IR","type":"education","lineage":["https://openalex.org/I55547365"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Fayyaz Heydari, Kazem","raw_affiliation_strings":["Department of Statistics, Payame Noor University, Tehran, Iran"],"raw_orcid":"https://orcid.org/0000-0001-7928-3741","affiliations":[{"raw_affiliation_string":"Department of Statistics, Payame Noor University, Tehran, Iran","institution_ids":["https://openalex.org/I55547365"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Momeni, Fereshteh","orcid":"https://orcid.org/0000-0003-4412-5457"},"institutions":[{"id":"https://openalex.org/I4210139126","display_name":"University of Science and Technology of Mazandaran","ror":"https://ror.org/04jf6jw55","country_code":"IR","type":"education","lineage":["https://openalex.org/I4210139126"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Momeni, Fereshteh","raw_affiliation_strings":["Department of Mathematics and Statistics, Behshahr Branch, Islamic Azad University, Behshahr, Iran"],"raw_orcid":"https://orcid.org/0000-0003-4412-5457","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Behshahr Branch, Islamic Azad University, Behshahr, Iran","institution_ids":["https://openalex.org/I4210139126"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yaghoobzadeh Sharastani, Shahram","orcid":"https://orcid.org/0000-0002-8794-2222"},"institutions":[{"id":"https://openalex.org/I55547365","display_name":"Payame Noor University","ror":"https://ror.org/031699d98","country_code":"IR","type":"education","lineage":["https://openalex.org/I55547365"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Yaghoobzadeh Sharastani, Shahram","raw_affiliation_strings":["Department of Statistics, Payame Noor University, Tehran, Iran"],"raw_orcid":"https://orcid.org/0000-0002-8794-2222","affiliations":[{"raw_affiliation_string":"Department of Statistics, Payame Noor University, Tehran, Iran","institution_ids":["https://openalex.org/I55547365"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55547365"],"apc_list":{"value":2600,"currency":"USD","value_usd":2600},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.63569703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.004600000102072954,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.002400000113993883,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weibull-distribution","display_name":"Weibull distribution","score":0.7299000024795532},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6944000124931335},{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.6022999882698059},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5144000053405762},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.49149999022483826},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.4447000026702881},{"id":"https://openalex.org/keywords/scale-parameter","display_name":"Scale parameter","score":0.38589999079704285}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7935000061988831},{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.7299000024795532},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6944000124931335},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6402999758720398},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.6022999882698059},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5144000053405762},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.4447000026702881},{"id":"https://openalex.org/C91716921","wikidata":"https://www.wikidata.org/wiki/Q1289366","display_name":"Scale parameter","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.3822000026702881},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3734999895095825},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C199435849","wikidata":"https://www.wikidata.org/wiki/Q3179293","display_name":"Shape parameter","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.27810001373291016},{"id":"https://openalex.org/C95770405","wikidata":"https://www.wikidata.org/wiki/Q5421539","display_name":"Exponentiated Weibull distribution","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2549000084400177},{"id":"https://openalex.org/C98385598","wikidata":"https://www.wikidata.org/wiki/Q1339385","display_name":"Empirical distribution function","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.71602/tfss.2026.1200900","is_oa":true,"landing_page_url":"https://doi.org/10.71602/tfss.2026.1200900","pdf_url":null,"source":{"id":"https://openalex.org/S169411308","display_name":"Fuzzy Sets and Systems","issn_l":"0165-0114","issn":["0165-0114","1872-6801"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.71602/tfss.2026.1200900","is_oa":true,"landing_page_url":"https://doi.org/10.71602/tfss.2026.1200900","pdf_url":null,"source":{"id":"https://openalex.org/S169411308","display_name":"Fuzzy Sets and Systems","issn_l":"0165-0114","issn":["0165-0114","1872-6801"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4961327612400055,"id":"https://metadata.un.org/sdg/16"},{"display_name":"Reduced inequalities","score":0.43403005599975586,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"examines":[2],"Bayesian,":[3],"E-Bayesian":[4],"(E-B),":[5],"and":[6,31,36,64,83,96,109],"hierarchical":[7],"Bayesian":[8,108],"(H-B)":[9],"estimation":[10],"methods":[11],"for":[12],"the":[13,23,58,85,88,101,107,113],"stress-strength":[14],"reliability":[15],"parameter":[16],"(SSRP)":[17],"R":[18],"=":[19],"P(X&gt;Y":[20],"),":[21],"within":[22],"Weibull":[24,43],"distribution":[25],"framework":[26],"under":[27,112],"Type":[28],"II":[29],"censoring":[30],"fuzzy":[32],"data":[33,75],"conditions.":[34],"Stress":[35],"strength":[37],"random":[38],"variables":[39],"are":[40,55],"modeled":[41],"as":[42],"distributions":[44],"with":[45],"distinct":[46],"scale":[47],"parameters":[48],"but":[49],"a":[50,68],"common":[51],"shape":[52],"parameter.":[53],"Estimations":[54],"conducted":[56],"using":[57],"squared":[59,114],"error":[60,115],"(SE)":[61,116],"loss":[62,117],"function":[63],"Lindleys":[65],"approximation.":[66],"Furthermore,":[67],"comprehensive":[69],"simulation":[70,95],"study,":[71],"complemented":[72],"by":[73],"real-world":[74],"analysis,":[76],"has":[77],"been":[78],"carried":[79],"out":[80],"to":[81],"assess":[82],"compare":[84],"performance":[86],"of":[87],"proposed":[89],"estimators.":[90],"The":[91],"results":[92],"from":[93],"both":[94,106],"empirical":[97],"analyses":[98],"demonstrate":[99],"that":[100],"H-B":[102],"estimator":[103],"consistently":[104],"outperforms":[105],"E-B":[110],"estimators":[111],"function.":[118]},"counts_by_year":[],"updated_date":"2025-11-13T11:05:06.444514","created_date":"2025-11-13T00:00:00"}
