{"id":"https://openalex.org/W1967141380","doi":"https://doi.org/10.2481/dsj.012-004","title":"Bayesian Estimation in the Proportional Hazards Model of Random Censorship under Asymmetric Loss Functions","display_name":"Bayesian Estimation in the Proportional Hazards Model of Random Censorship under Asymmetric Loss Functions","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W1967141380","doi":"https://doi.org/10.2481/dsj.012-004","mag":"1967141380"},"language":"en","primary_location":{"id":"doi:10.2481/dsj.012-004","is_oa":true,"landing_page_url":"https://doi.org/10.2481/dsj.012-004","pdf_url":null,"source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.2481/dsj.012-004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068647076","display_name":"Muhammad Yameen Danish","orcid":null},"institutions":[{"id":"https://openalex.org/I181355716","display_name":"Allama Iqbal Open University","ror":"https://ror.org/04vympt94","country_code":"PK","type":"education","lineage":["https://openalex.org/I181355716"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Muhammad Yameen Danish","raw_affiliation_strings":["Department of Mathematics & Statistics, Allama Iqbal Open University, Islamabad, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics & Statistics, Allama Iqbal Open University, Islamabad, Pakistan","institution_ids":["https://openalex.org/I181355716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101953752","display_name":"Muhammad Aslam","orcid":"https://orcid.org/0000-0003-3355-2330"},"institutions":[{"id":"https://openalex.org/I12469534","display_name":"Quaid-i-Azam University","ror":"https://ror.org/04s9hft57","country_code":"PK","type":"education","lineage":["https://openalex.org/I12469534"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Aslam","raw_affiliation_strings":["Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan;"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan;","institution_ids":["https://openalex.org/I12469534"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068647076"],"corresponding_institution_ids":["https://openalex.org/I181355716"],"apc_list":{"value":350,"currency":"GBP","value_usd":429},"apc_paid":{"value":350,"currency":"GBP","value_usd":429},"fwci":0.3067,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.58036137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"11","issue":"0","first_page":"72","last_page":"88"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9990000128746033,"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/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.762677013874054},{"id":"https://openalex.org/keywords/weibull-distribution","display_name":"Weibull distribution","score":0.6953957676887512},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6675691604614258},{"id":"https://openalex.org/keywords/conjugate-prior","display_name":"Conjugate prior","score":0.5755877494812012},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5722587704658508},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5702544450759888},{"id":"https://openalex.org/keywords/bayes-estimator","display_name":"Bayes estimator","score":0.5284276604652405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5179387927055359},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5071685314178467},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.49977612495422363},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44633281230926514},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3528027832508087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3324725329875946}],"concepts":[{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.762677013874054},{"id":"https://openalex.org/C173291955","wikidata":"https://www.wikidata.org/wiki/Q732332","display_name":"Weibull distribution","level":2,"score":0.6953957676887512},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6675691604614258},{"id":"https://openalex.org/C26004113","wikidata":"https://www.wikidata.org/wiki/Q3711784","display_name":"Conjugate prior","level":4,"score":0.5755877494812012},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5722587704658508},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5702544450759888},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.5284276604652405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5179387927055359},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5071685314178467},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.49977612495422363},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44633281230926514},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3528027832508087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3324725329875946}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2481/dsj.012-004","is_oa":true,"landing_page_url":"https://doi.org/10.2481/dsj.012-004","pdf_url":null,"source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science Journal","raw_type":"journal-article"},{"id":"pmh:oai:ojs.datascience.codata.org:article/49","is_oa":true,"landing_page_url":"https://datascience.codata.org/jms/article/view/dsj.012-004","pdf_url":null,"source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science Journal; Vol 11 (2012); 72-88","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.2481/dsj.012-004","is_oa":true,"landing_page_url":"https://doi.org/10.2481/dsj.012-004","pdf_url":null,"source":{"id":"https://openalex.org/S62969111","display_name":"Data Science Journal","issn_l":"1683-1470","issn":["1683-1470"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320511","host_organization_name":"Ubiquity Press","host_organization_lineage":["https://openalex.org/P4310320511"],"host_organization_lineage_names":["Ubiquity Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science Journal","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"},{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1533191897","https://openalex.org/W1590680336","https://openalex.org/W1965040604","https://openalex.org/W1995920178","https://openalex.org/W2006189613","https://openalex.org/W2014766989","https://openalex.org/W2020875674","https://openalex.org/W2020999234","https://openalex.org/W2021279320","https://openalex.org/W2026931018","https://openalex.org/W2038585456","https://openalex.org/W2057868807","https://openalex.org/W2084738107","https://openalex.org/W2087615897","https://openalex.org/W2121090677","https://openalex.org/W2139024323","https://openalex.org/W2140084649","https://openalex.org/W2318085879","https://openalex.org/W2489876217","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4298870584","https://openalex.org/W2734174941","https://openalex.org/W4306291977","https://openalex.org/W2950950409","https://openalex.org/W2085834335","https://openalex.org/W2072169887","https://openalex.org/W4298441262","https://openalex.org/W2404382874","https://openalex.org/W2232589144","https://openalex.org/W2378181005"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,45],"consider":[4],"the":[5,11,19,31,40,48,54,69,81,84,100,115],"Bayesian":[6],"estimation":[7],"of":[8,15,83,118],"parameters":[9,41],"in":[10],"proportional":[12],"hazards":[13],"model":[14,55],"random":[16],"censorship":[17],"for":[18,30,87,92,129],"Weibull":[20,32],"distribution":[21,33],"under":[22,59,103],"different":[23,88,93],"asymmetric":[24],"loss":[25,64,108,120],"functions.":[26],"It":[27,96],"is":[28,76,97,127],"well-known":[29],"that":[34,99],"a":[35],"joint":[36],"conjugate":[37],"prior":[38],"on":[39,53],"does":[42],"not":[43],"exist;":[44],"use":[46],"both":[47],"informative":[49],"and":[50,61,91,105],"noninformative":[51],"priors":[52],"parameters.":[56,95,122],"Bayes":[57,101],"estimates":[58],"LINEX":[60,104],"general":[62,106],"entropy":[63,107],"functions":[65,109],"are":[66],"obtained":[67],"using":[68],"Gibbs":[70],"sampling":[71],"scheme.":[72],"A":[73],"simulation":[74],"study":[75],"carried":[77],"out":[78],"to":[79],"observe":[80],"behavior":[82],"proposed":[85],"estimators":[86,102],"sample":[89],"sizes":[90],"censoring":[94],"observed":[98],"can":[110],"be":[111],"used":[112],"effectively":[113],"with":[114],"appropriate":[116],"choice":[117],"respective":[119],"function":[121],"One":[123],"real":[124],"data":[125],"set":[126],"analyzed":[128],"illustrative":[130],"purposes.":[131]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}