{"id":"https://openalex.org/W4200043869","doi":"https://doi.org/10.1080/03610918.2021.2018460","title":"Estimation of Lindley constant-stress model via product of spacing with Type-II censored accelerated life data","display_name":"Estimation of Lindley constant-stress model via product of spacing with Type-II censored accelerated life data","publication_year":2021,"publication_date":"2021-12-22","ids":{"openalex":"https://openalex.org/W4200043869","doi":"https://doi.org/10.1080/03610918.2021.2018460"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2021.2018460","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.2018460","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","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/A5061752442","display_name":"Mazen Nassar","orcid":"https://orcid.org/0000-0002-6353-2245"},"institutions":[{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]},{"id":"https://openalex.org/I192398990","display_name":"Zagazig University","ror":"https://ror.org/053g6we49","country_code":"EG","type":"education","lineage":["https://openalex.org/I192398990"]}],"countries":["EG","SA"],"is_corresponding":true,"raw_author_name":"Mazen Nassar","raw_affiliation_strings":["Department of Statistics, Faculty of Commerce, Zagazig University, Zagazig, Egypt","Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Commerce, Zagazig University, Zagazig, Egypt","institution_ids":["https://openalex.org/I192398990"]},{"raw_affiliation_string":"Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia","institution_ids":["https://openalex.org/I185163786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025115763","display_name":"Sanku Dey","orcid":"https://orcid.org/0000-0001-8523-8189"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanku Dey","raw_affiliation_strings":["Department of Statistics, St. Anthony\u2019s College, Shillong, Meghalaya, India","Department of Statistics, St. Anthony's College, Shillong, Meghalaya, India"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, St. Anthony\u2019s College, Shillong, Meghalaya, India","institution_ids":[]},{"raw_affiliation_string":"Department of Statistics, St. Anthony's College, Shillong, Meghalaya, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456514","display_name":"Liang Wang","orcid":"https://orcid.org/0000-0002-2600-5112"},"institutions":[{"id":"https://openalex.org/I120825670","display_name":"Yunnan Normal University","ror":"https://ror.org/00sc9n023","country_code":"CN","type":"education","lineage":["https://openalex.org/I120825670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Wang","raw_affiliation_strings":["School of Mathematics, Yunnan Normal University, Kunming, P.R. China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics, Yunnan Normal University, Kunming, P.R. China","institution_ids":["https://openalex.org/I120825670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055103172","display_name":"Ahmed Elshahhat","orcid":"https://orcid.org/0000-0002-9916-259X"},"institutions":[{"id":"https://openalex.org/I192398990","display_name":"Zagazig University","ror":"https://ror.org/053g6we49","country_code":"EG","type":"education","lineage":["https://openalex.org/I192398990"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed Elshahhat","raw_affiliation_strings":["Faculty of Technology and Development, Zagazig University, Zagazig, Egypt"],"affiliations":[{"raw_affiliation_string":"Faculty of Technology and Development, Zagazig University, Zagazig, Egypt","institution_ids":["https://openalex.org/I192398990"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5061752442"],"corresponding_institution_ids":["https://openalex.org/I185163786","https://openalex.org/I192398990"],"apc_list":null,"apc_paid":null,"fwci":5.2039,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.96730536,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"53","issue":"1","first_page":"288","last_page":"314"},"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9818999767303467,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/frequentist-inference","display_name":"Frequentist inference","score":0.8375647068023682},{"id":"https://openalex.org/keywords/accelerated-life-testing","display_name":"Accelerated life testing","score":0.8290762901306152},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.592383861541748},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5687402486801147},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5417528748512268},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5130051970481873},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.5086641907691956},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.42972826957702637},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.41136854887008667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3894225060939789},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.3541160821914673},{"id":"https://openalex.org/keywords/weibull-distribution","display_name":"Weibull distribution","score":0.18305522203445435},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.07867103815078735}],"concepts":[{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.8375647068023682},{"id":"https://openalex.org/C158379689","wikidata":"https://www.wikidata.org/wiki/Q3533504","display_name":"Accelerated life testing","level":3,"score":0.8290762901306152},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.592383861541748},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5687402486801147},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5417528748512268},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5130051970481873},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5086641907691956},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.42972826957702637},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.41136854887008667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3894225060939789},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3541160821914673},{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.18305522203445435},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.07867103815078735},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2021.2018460","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2021.2018460","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1527171679","https://openalex.org/W1965894208","https://openalex.org/W2020002779","https://openalex.org/W2023219679","https://openalex.org/W2065691010","https://openalex.org/W2084568079","https://openalex.org/W2090001193","https://openalex.org/W2106536783","https://openalex.org/W2108690596","https://openalex.org/W2116913389","https://openalex.org/W2411262377","https://openalex.org/W2428472680","https://openalex.org/W2467305554","https://openalex.org/W2495741403","https://openalex.org/W2591193890","https://openalex.org/W2619995254","https://openalex.org/W2790092024","https://openalex.org/W2884849372","https://openalex.org/W2904579171","https://openalex.org/W2914468048","https://openalex.org/W2958556832","https://openalex.org/W2971867460","https://openalex.org/W2982002839","https://openalex.org/W3003925851","https://openalex.org/W3113278671","https://openalex.org/W3128601705","https://openalex.org/W3139060137","https://openalex.org/W3171893673","https://openalex.org/W3194474831","https://openalex.org/W3213881051","https://openalex.org/W4233921518","https://openalex.org/W7037411764","https://openalex.org/W7044785239"],"related_works":["https://openalex.org/W88131178","https://openalex.org/W2290754432","https://openalex.org/W2089224781","https://openalex.org/W232830309","https://openalex.org/W3006840100","https://openalex.org/W2089359439","https://openalex.org/W2120595071","https://openalex.org/W2499041866","https://openalex.org/W4376166778","https://openalex.org/W4386222676"],"abstract_inverted_index":{"Accelerated":[0],"Life":[1],"Test":[2],"has":[3],"been":[4],"introduced":[5],"as":[6,83,103,130,132],"a":[7],"tool":[8],"to":[9,107,162,171,184],"aid":[10],"in":[11],"obtaining":[12],"sufficient":[13],"failure":[14],"time":[15],"data":[16,64,181],"of":[17,31,59,87,121,147,166,188],"test":[18,180],"units":[19,32],"quickly":[20],"and":[21,45,56,96,118,141,150],"extrapolating":[22],"lifetime":[23,30],"information":[24],"under":[25,65,100],"use":[26],"conditions.":[27],"When":[28],"the":[29,36,39,42,46,71,75,84,94,97,108,133,137,148,164,167,173,186,189],"is":[33,90],"distributed":[34],"by":[35],"Lindley":[37],"model,":[38],"estimations":[40],"for":[41,92,127],"unknown":[43,128],"parameters":[44,95,129,149],"reliability":[47,98,134,151],"function":[48,99,152],"are":[49,125,153,160,182],"established":[50],"based":[51],"on":[52],"two":[53,176],"frequentist":[54,72],"methods":[55],"Bayesian":[57,113,123],"method":[58,89],"estimation":[60],"using":[61],"Type-II":[62],"censored":[63],"constant-stress":[66],"accelerated":[67,178],"life":[68,179],"test.":[69],"In":[70,112],"methods,":[73],"besides,":[74],"conventional":[76],"likelihood-based":[77],"estimation,":[78,114],"another":[79],"competitive":[80],"method,":[81],"known":[82],"maximum":[85,116,119],"product":[86,120],"spacing":[88],"proposed":[91,168,174,190],"estimating":[93],"normal":[101],"conditions":[102],"an":[104],"alternative":[105],"approach":[106],"common":[109],"likelihood":[110,117],"method.":[111],"both":[115],"spacing-based":[122],"estimates":[124],"discussed":[126],"well":[131],"function.":[135],"Moreover,":[136],"approximate":[138],"confidence":[139],"intervals":[140,146],"highest":[142],"posterior":[143],"density":[144],"credible":[145],"also":[154],"obtained.":[155],"Extensive":[156],"Monte-Carlo":[157],"simulation":[158],"studies":[159],"conducted":[161],"evaluate":[163],"performance":[165],"estimates.":[169],"Finally,":[170],"demonstrate":[172],"methodology,":[175],"real-life":[177],"considered":[183],"show":[185],"applicabilities":[187],"methods.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}