{"id":"https://openalex.org/W2340355299","doi":"https://doi.org/10.3233/mas-150358","title":"Bayesian inference and prediction for generalized inverted exponential distribution for Type-II censored data","display_name":"Bayesian inference and prediction for generalized inverted exponential distribution for Type-II censored data","publication_year":2016,"publication_date":"2016-04-14","ids":{"openalex":"https://openalex.org/W2340355299","doi":"https://doi.org/10.3233/mas-150358","mag":"2340355299"},"language":"en","primary_location":{"id":"doi:10.3233/mas-150358","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-150358","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025115763","display_name":"Sanku Dey","orcid":"https://orcid.org/0000-0001-8523-8189"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sanku Dey","raw_affiliation_strings":["Department of Statistics, St. Anthony's College, Shillong, Meghalaya, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, St. Anthony's College, Shillong, Meghalaya, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091174578","display_name":"Tanujit Dey","orcid":"https://orcid.org/0000-0001-5559-211X"},"institutions":[{"id":"https://openalex.org/I1316902750","display_name":"Cleveland Clinic","ror":"https://ror.org/03xjacd83","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1316902750"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tanujit Dey","raw_affiliation_strings":["Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA","institution_ids":["https://openalex.org/I1316902750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023502362","display_name":"Daniel Vasiliu","orcid":null},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Vasiliu","raw_affiliation_strings":["Department of Mathematics, College of William and Mary, Williamsburg, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of William and Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025115763"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.036945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"2","first_page":"125","last_page":"136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9969000220298767,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9803000092506409,"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/prior-probability","display_name":"Prior probability","score":0.721872866153717},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.6626080274581909},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5947820544242859},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5894361734390259},{"id":"https://openalex.org/keywords/exponential-distribution","display_name":"Exponential distribution","score":0.5384509563446045},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5369974970817566},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.532073974609375},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.4800904393196106},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.4614905118942261},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4562162458896637},{"id":"https://openalex.org/keywords/metropolis\u2013hastings-algorithm","display_name":"Metropolis\u2013Hastings algorithm","score":0.4531479477882385},{"id":"https://openalex.org/keywords/bayes-factor","display_name":"Bayes factor","score":0.4515230059623718},{"id":"https://openalex.org/keywords/gamma-distribution","display_name":"Gamma distribution","score":0.42997342348098755},{"id":"https://openalex.org/keywords/bayesian-linear-regression","display_name":"Bayesian linear regression","score":0.4266435205936432},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4160791337490082},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4124208390712738},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.382550448179245},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.2772235572338104}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.721872866153717},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.6626080274581909},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5947820544242859},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5894361734390259},{"id":"https://openalex.org/C55350006","wikidata":"https://www.wikidata.org/wiki/Q237193","display_name":"Exponential distribution","level":2,"score":0.5384509563446045},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5369974970817566},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.532073974609375},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.4800904393196106},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.4614905118942261},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4562162458896637},{"id":"https://openalex.org/C204693719","wikidata":"https://www.wikidata.org/wiki/Q910810","display_name":"Metropolis\u2013Hastings algorithm","level":4,"score":0.4531479477882385},{"id":"https://openalex.org/C142291917","wikidata":"https://www.wikidata.org/wiki/Q4165283","display_name":"Bayes factor","level":4,"score":0.4515230059623718},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.42997342348098755},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.4266435205936432},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4160791337490082},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4124208390712738},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.382550448179245},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.2772235572338104},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/mas-150358","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-150358","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W128815223","https://openalex.org/W1496753898","https://openalex.org/W1542459729","https://openalex.org/W1988520084","https://openalex.org/W2024315245","https://openalex.org/W2055779904","https://openalex.org/W2056864963","https://openalex.org/W2065704097","https://openalex.org/W2073385762","https://openalex.org/W2073648583","https://openalex.org/W2084568079","https://openalex.org/W2101310066","https://openalex.org/W2137048831","https://openalex.org/W2162803334"],"related_works":["https://openalex.org/W2058297408","https://openalex.org/W568881065","https://openalex.org/W2018805755","https://openalex.org/W2973802835","https://openalex.org/W2419098430","https://openalex.org/W1988119291","https://openalex.org/W784871970","https://openalex.org/W185305075","https://openalex.org/W2035819464","https://openalex.org/W1597397274"],"abstract_inverted_index":{"The":[0],"manuscript":[1],"introduces":[2],"Bayesian":[3,25],"estimation":[4,26],"and":[5,42,53,70,85],"prediction":[6],"of":[7,11,27,46,98,112],"a":[8,50,119,123],"generalized":[9],"version":[10],"the":[12,24,28,32,40,43,47,60,71,86,96,99,108],"inverted":[13],"exponential":[14],"distribution":[15,48],"for":[16,132],"Type-II":[17],"censored":[18],"data.":[19],"It":[20],"further":[21],"reflects":[22],"on":[23],"unknown":[29],"parameters":[30,45],"under":[31],"squared":[33],"error":[34],"loss":[35],"function,":[36],"assuming":[37],"that":[38],"both":[39],"scale":[41],"shape":[44],"have":[49],"gamma":[51],"prior":[52],"are":[54,79,92],"independently":[55],"distributed.":[56],"Under":[57],"these":[58],"priors,":[59],"importance":[61],"sampling":[62],"technique":[63],"is":[64,130],"used":[65],"to":[66,94,106],"calculate":[67],"Bayes":[68,77,101],"estimates":[69,78],"corresponding":[72],"highest":[73],"posterior":[74,109],"density":[75,111],"intervals.":[76],"also":[80],"computed":[81],"using":[82],"Lindley's":[83],"approximation":[84],"Metropolis-Hastings":[87],"algorithm.":[88],"Monte":[89],"Carlo":[90],"simulations":[91],"performed":[93,131],"compare":[95],"performance":[97],"proposed":[100],"estimates.":[102],"This":[103],"article":[104],"seeks":[105],"extend":[107],"predictive":[110,120],"future":[113],"observations,":[114],"as":[115,117],"well":[116],"construct":[118],"interval":[121],"with":[122],"given":[124],"coverage":[125],"probability.":[126],"A":[127],"data":[128],"analysis":[129],"illustrative":[133],"purposes.":[134]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}