{"id":"https://openalex.org/W2961635899","doi":"https://doi.org/10.1080/03610918.2019.1639734","title":"Estimation procedures for Kumaraswamy distribution parameters under adaptive type-II hybrid progressive censoring","display_name":"Estimation procedures for Kumaraswamy distribution parameters under adaptive type-II hybrid progressive censoring","publication_year":2019,"publication_date":"2019-07-12","ids":{"openalex":"https://openalex.org/W2961635899","doi":"https://doi.org/10.1080/03610918.2019.1639734","mag":"2961635899"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1639734","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1639734","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/A5056501632","display_name":"Akram Kohansal","orcid":"https://orcid.org/0000-0002-1894-411X"},"institutions":[{"id":"https://openalex.org/I69425150","display_name":"Imam Khomeini International University","ror":"https://ror.org/02jeykk09","country_code":"IR","type":"education","lineage":["https://openalex.org/I69425150"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Akram Kohansal","raw_affiliation_strings":["Department of Statistics, Imam Khomeini International University, Qazvin, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Imam Khomeini International University, Qazvin, Iran","institution_ids":["https://openalex.org/I69425150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037023360","display_name":"Hassan S. Bakouch","orcid":"https://orcid.org/0000-0002-3189-0670"},"institutions":[{"id":"https://openalex.org/I21376657","display_name":"Tanta University","ror":"https://ror.org/016jp5b92","country_code":"EG","type":"education","lineage":["https://openalex.org/I21376657"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Hassan S. Bakouch","raw_affiliation_strings":["Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt","institution_ids":["https://openalex.org/I21376657"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056501632"],"corresponding_institution_ids":["https://openalex.org/I69425150"],"apc_list":null,"apc_paid":null,"fwci":1.3573,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.82834115,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"50","issue":"12","first_page":"4059","last_page":"4078"},"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/T11186","display_name":"Hydrology and Drought Analysis","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9751999974250793,"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/censoring","display_name":"Censoring (clinical trials)","score":0.7966163754463196},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7077174782752991},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.652535080909729},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.5843533873558044},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.5817676782608032},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5131614804267883},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.49980759620666504},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.49535977840423584},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4779653251171112},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4490450620651245},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.43594303727149963},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.4149829149246216},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36045101284980774},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35604381561279297},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.29031533002853394}],"concepts":[{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.7966163754463196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7077174782752991},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.652535080909729},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.5843533873558044},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5817676782608032},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5131614804267883},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.49980759620666504},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.49535977840423584},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4779653251171112},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4490450620651245},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.43594303727149963},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.4149829149246216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36045101284980774},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35604381561279297},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.29031533002853394}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2019.1639734","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1639734","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1569673102","https://openalex.org/W1968366913","https://openalex.org/W1989240328","https://openalex.org/W2028812304","https://openalex.org/W2043415670","https://openalex.org/W2048436063","https://openalex.org/W2049633694","https://openalex.org/W2066608222","https://openalex.org/W2076065380","https://openalex.org/W2078961069","https://openalex.org/W2086693579","https://openalex.org/W2124181495","https://openalex.org/W2148440732","https://openalex.org/W2296589406","https://openalex.org/W2309478052","https://openalex.org/W2556801994","https://openalex.org/W2742708508","https://openalex.org/W2806944458","https://openalex.org/W2895640080","https://openalex.org/W3119264854","https://openalex.org/W3125005510","https://openalex.org/W4232535126"],"related_works":["https://openalex.org/W1975401047","https://openalex.org/W4210616617","https://openalex.org/W3180984448","https://openalex.org/W4308885088","https://openalex.org/W3042703790","https://openalex.org/W2898936165","https://openalex.org/W2054283672","https://openalex.org/W1974564696","https://openalex.org/W4313470123","https://openalex.org/W2961635899"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,9,17,27,33,51,55,58,70,74,80,92,98,106,111,119],"point":[4],"and":[5,42,57,87,122],"interval":[6],"estimation":[7,30,72],"of":[8,12,32,54,73,94,105],"unknown":[10],"parameters":[11,34,56,75,107],"Kumaraswamy":[13],"(Ku)":[14],"distribution":[15,53],"under":[16],"adaptive":[18],"Type-II":[19],"hybrid":[20],"progressive":[21],"censored":[22],"samples.":[23],"First,":[24],"we":[25,49],"obtain":[26],"maximum":[28],"likelihood":[29],"(MLE)":[31],"using":[35,79],"Newton-Raphson":[36],"(NR)":[37],"method,":[38],"expectation":[39],"maximization":[40],"(EM)":[41],"stochastic":[43],"EM":[44],"(SEM)":[45],"algorithms.":[46],"In":[47],"addition,":[48],"derive":[50],"asymptotic":[52,59],"confidence":[60,65],"intervals.":[61],"Moreover,":[62],"two":[63],"bootstrap":[64],"intervals":[66,104],"are":[67,108],"achieved.":[68],"Second,":[69],"Bayesian":[71],"is":[76,127],"approximated":[77],"by":[78,118],"Markov":[81],"Chain":[82],"Monte":[83],"Carlo":[84],"(MCMC)":[85],"algorithm":[86],"Lindley\u2019s":[88],"method":[89],"due":[90],"to":[91,129],"lack":[93],"explicit":[95],"forms.":[96],"Furthermore,":[97],"highest":[99],"posterior":[100],"density":[101],"(HPD)":[102],"credible":[103],"derived.":[109],"Finally,":[110],"different":[112],"proposed":[113],"estimations":[114],"have":[115],"been":[116],"compared":[117],"simulation":[120],"studies":[121],"a":[123],"practical":[124],"data":[125],"set":[126],"analyzed":[128],"illustrative":[130],"aims.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}