{"id":"https://openalex.org/W4214880415","doi":"https://doi.org/10.1080/03610918.2022.2045498","title":"Inference on the lifetime performance index of gamma distribution: point and interval estimation","display_name":"Inference on the lifetime performance index of gamma distribution: point and interval estimation","publication_year":2022,"publication_date":"2022-03-02","ids":{"openalex":"https://openalex.org/W4214880415","doi":"https://doi.org/10.1080/03610918.2022.2045498"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2045498","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2045498","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/A5010156624","display_name":"Javad Shaabani","orcid":null},"institutions":[{"id":"https://openalex.org/I112536369","display_name":"Yazd University","ror":"https://ror.org/02x99ac45","country_code":"IR","type":"education","lineage":["https://openalex.org/I112536369"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"J. Shaabani","raw_affiliation_strings":["Department of Statistics, Yazd University","Department of Statistics, Yazd University, Yazd, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Yazd University","institution_ids":["https://openalex.org/I112536369"]},{"raw_affiliation_string":"Department of Statistics, Yazd University, Yazd, Iran","institution_ids":["https://openalex.org/I112536369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045787539","display_name":"Ali Akbar Jafari","orcid":"https://orcid.org/0000-0002-2980-338X"},"institutions":[{"id":"https://openalex.org/I112536369","display_name":"Yazd University","ror":"https://ror.org/02x99ac45","country_code":"IR","type":"education","lineage":["https://openalex.org/I112536369"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"A. A. Jafari","raw_affiliation_strings":["Department of Statistics, Yazd University","Department of Statistics, Yazd University, Yazd, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Yazd University","institution_ids":["https://openalex.org/I112536369"]},{"raw_affiliation_string":"Department of Statistics, Yazd University, Yazd, Iran","institution_ids":["https://openalex.org/I112536369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045787539"],"corresponding_institution_ids":["https://openalex.org/I112536369"],"apc_list":null,"apc_paid":null,"fwci":0.9307,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77399422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"53","issue":"3","first_page":"1368","last_page":"1386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9991999864578247,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9984999895095825,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9944999814033508,"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/estimator","display_name":"Estimator","score":0.8119487762451172},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.7851428985595703},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.7469955086708069},{"id":"https://openalex.org/keywords/coverage-probability","display_name":"Coverage probability","score":0.6474099159240723},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.6471473574638367},{"id":"https://openalex.org/keywords/confidence-distribution","display_name":"Confidence distribution","score":0.5947367548942566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5856728553771973},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.547137975692749},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.513388991355896},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.45942333340644836},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.45332425832748413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.27288731932640076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08334892988204956}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8119487762451172},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.7851428985595703},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7469955086708069},{"id":"https://openalex.org/C2776292839","wikidata":"https://www.wikidata.org/wiki/Q5179217","display_name":"Coverage probability","level":3,"score":0.6474099159240723},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.6471473574638367},{"id":"https://openalex.org/C13662513","wikidata":"https://www.wikidata.org/wiki/Q5160087","display_name":"Confidence distribution","level":3,"score":0.5947367548942566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5856728553771973},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.547137975692749},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.513388991355896},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.45942333340644836},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.45332425832748413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.27288731932640076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08334892988204956}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2022.2045498","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2045498","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W128815223","https://openalex.org/W1978901782","https://openalex.org/W1996399172","https://openalex.org/W2007636595","https://openalex.org/W2033092527","https://openalex.org/W2046262695","https://openalex.org/W2048080993","https://openalex.org/W2050609606","https://openalex.org/W2062529663","https://openalex.org/W2070290114","https://openalex.org/W2088038447","https://openalex.org/W2089848228","https://openalex.org/W2094228883","https://openalex.org/W2112326444","https://openalex.org/W2130999833","https://openalex.org/W2428472680","https://openalex.org/W2482654751","https://openalex.org/W2526298724","https://openalex.org/W2573107880","https://openalex.org/W2589471818","https://openalex.org/W2593614095","https://openalex.org/W2612159777","https://openalex.org/W2795512730","https://openalex.org/W2797026095","https://openalex.org/W2889450932","https://openalex.org/W2899911121","https://openalex.org/W2904177731","https://openalex.org/W2914116596","https://openalex.org/W2928864551","https://openalex.org/W2930644217","https://openalex.org/W2979458700","https://openalex.org/W3034452723","https://openalex.org/W3047354618","https://openalex.org/W3118695577","https://openalex.org/W3126281209","https://openalex.org/W3131850962","https://openalex.org/W3170367384","https://openalex.org/W3191448538","https://openalex.org/W3191994658","https://openalex.org/W3198157392","https://openalex.org/W4200236646","https://openalex.org/W4200364249","https://openalex.org/W4200463526","https://openalex.org/W4230651318","https://openalex.org/W4235618618","https://openalex.org/W6992022558"],"related_works":["https://openalex.org/W1489574876","https://openalex.org/W2153721965","https://openalex.org/W1975401047","https://openalex.org/W2810596480","https://openalex.org/W4256568980","https://openalex.org/W4225113063","https://openalex.org/W2032811365","https://openalex.org/W4200171716","https://openalex.org/W1992991918","https://openalex.org/W4214880415"],"abstract_inverted_index":{"Performance":[0],"capability":[1,76],"indices":[2],"are":[3,50,71],"valuable":[4],"measures":[5],"to":[6,84,104],"evaluate":[7],"the":[8,25,42,58,74,86,95,106],"quality":[9],"of":[10,41,88,94],"a":[11,20,29],"product.":[12],"In":[13],"this":[14],"paper,":[15],"we":[16],"consider":[17],"inference":[18],"on":[19],"lifetime":[21,27],"performance":[22,75],"index":[23],"when":[24],"product\u2019s":[26],"follows":[28],"gamma":[30],"distribution":[31],"with":[32],"unknown":[33],"parameters.":[34],"The":[35],"bias":[36],"and":[37,46,66,91,108],"mean":[38],"square":[39],"error":[40],"maximum":[43,59],"likelihood":[44,60],"estimator":[45],"other":[47],"proposed":[48],"estimators":[49,107],"compared.":[51],"Also,":[52],"an":[53],"asymptotic":[54],"confidence":[55,64,96,109],"interval":[56],"using":[57],"estimator,":[61],"thirteen":[62],"bootstrap":[63],"intervals,":[65],"four":[67],"generalized":[68],"pivotal":[69],"quantities":[70],"derived":[72],"for":[73],"index.":[77],"A":[78],"Monte":[79],"Carlo":[80],"simulation":[81],"is":[82,102],"provided":[83],"investigate":[85],"accuracy":[87],"expected":[89],"lengths":[90],"coverage":[92],"probabilities":[93],"intervals.":[97,110],"An":[98],"actual":[99],"data":[100],"set":[101],"used":[103],"illustrate":[105]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
