{"id":"https://openalex.org/W2921022534","doi":"https://doi.org/10.1080/03610918.2019.1577968","title":"Statistical inference based on left truncated and interval censored data from log-location-scale family of distributions","display_name":"Statistical inference based on left truncated and interval censored data from log-location-scale family of distributions","publication_year":2019,"publication_date":"2019-03-11","ids":{"openalex":"https://openalex.org/W2921022534","doi":"https://doi.org/10.1080/03610918.2019.1577968","mag":"2921022534"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2019.1577968","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1577968","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/A5007930424","display_name":"Debanjan Mitra","orcid":"https://orcid.org/0000-0003-3705-3141"},"institutions":[{"id":"https://openalex.org/I46130087","display_name":"Indian Institute of Management Udaipur","ror":"https://ror.org/001xs0312","country_code":"IN","type":"education","lineage":["https://openalex.org/I46130087"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Debanjan Mitra","raw_affiliation_strings":["Operations Management, Quantitative Methods and Information Systems Area, Indian Institute of Management Udaipur, Rajasthan, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Operations Management, Quantitative Methods and Information Systems Area, Indian Institute of Management Udaipur, Rajasthan, India","institution_ids":["https://openalex.org/I46130087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039956503","display_name":"N. Balakrishnan","orcid":"https://orcid.org/0000-0001-5842-8892"},"institutions":[{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Narayanaswamy Balakrishnan","raw_affiliation_strings":["Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada","institution_ids":["https://openalex.org/I98251732"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007930424"],"corresponding_institution_ids":["https://openalex.org/I46130087"],"apc_list":null,"apc_paid":null,"fwci":2.0359,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.87952604,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"50","issue":"4","first_page":"1073","last_page":"1093"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9980000257492065,"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":0.996999979019165,"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":0.7205647230148315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.704888105392456},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.6064140200614929},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.5836045742034912},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5375954508781433},{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.5262308120727539},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.5178956985473633},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5106382966041565},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5044292211532593},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4940939247608185},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4908212125301361},{"id":"https://openalex.org/keywords/interval-estimation","display_name":"Interval estimation","score":0.48240363597869873},{"id":"https://openalex.org/keywords/scale-parameter","display_name":"Scale parameter","score":0.4574631154537201},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.359688937664032},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.29117000102996826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.24614205956459045},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0834842324256897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.07861500978469849}],"concepts":[{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.7205647230148315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.704888105392456},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.6064140200614929},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5836045742034912},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5375954508781433},{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.5262308120727539},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.5178956985473633},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5106382966041565},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5044292211532593},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4940939247608185},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4908212125301361},{"id":"https://openalex.org/C205167067","wikidata":"https://www.wikidata.org/wiki/Q3300636","display_name":"Interval estimation","level":3,"score":0.48240363597869873},{"id":"https://openalex.org/C91716921","wikidata":"https://www.wikidata.org/wiki/Q1289366","display_name":"Scale parameter","level":2,"score":0.4574631154537201},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.359688937664032},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.29117000102996826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24614205956459045},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0834842324256897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.07861500978469849},{"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:10.1080/03610918.2019.1577968","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2019.1577968","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":[{"id":"https://metadata.un.org/sdg/10","score":0.5199999809265137,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.47999998927116394,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W42473135","https://openalex.org/W71007243","https://openalex.org/W82430312","https://openalex.org/W131857772","https://openalex.org/W1586962881","https://openalex.org/W1965031889","https://openalex.org/W1970767737","https://openalex.org/W1981335888","https://openalex.org/W1987075352","https://openalex.org/W1987957212","https://openalex.org/W1988894273","https://openalex.org/W2006452394","https://openalex.org/W2026587206","https://openalex.org/W2029761439","https://openalex.org/W2041701373","https://openalex.org/W2044425952","https://openalex.org/W2049633694","https://openalex.org/W2050341350","https://openalex.org/W2066608222","https://openalex.org/W2076065380","https://openalex.org/W2082321764","https://openalex.org/W2085252131","https://openalex.org/W2085780599","https://openalex.org/W2091381192","https://openalex.org/W2267111803","https://openalex.org/W2316622962","https://openalex.org/W2322523654","https://openalex.org/W2480530026","https://openalex.org/W2498094064","https://openalex.org/W2622626512","https://openalex.org/W3100010118","https://openalex.org/W3140250330","https://openalex.org/W4214512856","https://openalex.org/W4231310240","https://openalex.org/W4232029634","https://openalex.org/W4233162961","https://openalex.org/W4233462588"],"related_works":["https://openalex.org/W1023014886","https://openalex.org/W4388295416","https://openalex.org/W4240160801","https://openalex.org/W3046248604","https://openalex.org/W4366758761","https://openalex.org/W2363238130","https://openalex.org/W2890272140","https://openalex.org/W2027607589","https://openalex.org/W2076173359","https://openalex.org/W4230083912"],"abstract_inverted_index":{"Here,":[0],"left":[1],"truncated":[2],"and":[3,23,61,81],"interval":[4],"censored":[5],"data":[6],"are":[7,26,35,44,55,74,89,96],"analyzed":[8,97],"by":[9],"assuming":[10],"that":[11],"the":[12,38],"underlying":[13],"lifetime":[14],"distribution":[15],"belongs":[16],"to":[17],"log-location-scale":[18],"family.":[19],"In":[20],"particular,":[21],"lognormal":[22],"Weibull":[24],"models":[25],"considered.":[27],"Steps":[28],"of":[29,40,70],"stochastic":[30],"expectation":[31],"maximization":[32],"(St-EM)":[33],"algorithm":[34,77],"developed":[36],"for":[37,53,78,85,98],"estimation":[39,80],"model":[41],"parameters.":[42],"MLEs":[43],"also":[45,105],"obtained":[46],"using":[47,57],"Newton\u2013Raphson":[48],"method.":[49],"Asymptotic":[50],"confidence":[51,87],"intervals":[52,88],"parameters":[54],"constructed":[56],"missing":[58],"information":[59],"principle,":[60],"parametric":[62,82],"bootstrap":[63,83],"approach.":[64],"Through":[65],"a":[66],"simulation":[67],"study,":[68],"performances":[69],"proposed":[71],"inferential":[72],"methods":[73],"assessed.":[75],"St-EM":[76],"point":[79],"approach":[84],"constructing":[86],"recommended":[90],"under":[91],"this":[92],"setup.":[93],"Two":[94],"datasets":[95],"illustrative":[99],"purpose.":[100],"A":[101],"prediction":[102],"problem":[103],"is":[104],"discussed.":[106]},"counts_by_year":[{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
