{"id":"https://openalex.org/W2968499668","doi":"https://doi.org/10.1007/s00180-019-00917-8","title":"Sparse Bayesian variable selection in kernel probit model for analyzing high-dimensional data","display_name":"Sparse Bayesian variable selection in kernel probit model for analyzing high-dimensional data","publication_year":2019,"publication_date":"2019-08-13","ids":{"openalex":"https://openalex.org/W2968499668","doi":"https://doi.org/10.1007/s00180-019-00917-8","mag":"2968499668"},"language":"en","primary_location":{"id":"doi:10.1007/s00180-019-00917-8","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-019-00917-8","pdf_url":null,"source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","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/A5031142835","display_name":"Aijun Yang","orcid":"https://orcid.org/0000-0002-9166-4421"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aijun Yang","raw_affiliation_strings":["College of Economics and Management, Nanjing Forestry University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Economics and Management, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079518086","display_name":"Yuzhu Tian","orcid":"https://orcid.org/0000-0002-6173-0985"},"institutions":[{"id":"https://openalex.org/I167383011","display_name":"Henan University of Science and Technology","ror":"https://ror.org/05d80kz58","country_code":"CN","type":"education","lineage":["https://openalex.org/I167383011"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuzhu Tian","raw_affiliation_strings":["School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, China","institution_ids":["https://openalex.org/I167383011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067980996","display_name":"Yunxian Li","orcid":"https://orcid.org/0009-0004-9145-5488"},"institutions":[{"id":"https://openalex.org/I49185572","display_name":"Yunnan University of Finance And Economics","ror":"https://ror.org/04rhev598","country_code":"CN","type":"education","lineage":["https://openalex.org/I49185572"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunxian Li","raw_affiliation_strings":["School of Finance, Yunnan University of Finance and Economics, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Finance, Yunnan University of Finance and Economics, Kunming, China","institution_ids":["https://openalex.org/I49185572"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014734789","display_name":"Jin\u2010Guan Lin","orcid":"https://orcid.org/0000-0002-2304-1177"},"institutions":[{"id":"https://openalex.org/I206777745","display_name":"Nanjing Audit University","ror":"https://ror.org/04zj2bd87","country_code":"CN","type":"education","lineage":["https://openalex.org/I206777745"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinguan Lin","raw_affiliation_strings":["School of Statistics and Mathematics, Nanjing Audit University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Nanjing Audit University, Nanjing, China","institution_ids":["https://openalex.org/I206777745"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031142835"],"corresponding_institution_ids":["https://openalex.org/I167027274"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":null,"fwci":0.2891,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.66486044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"35","issue":"1","first_page":"245","last_page":"258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9987000226974487,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5751469135284424},{"id":"https://openalex.org/keywords/bayesian-linear-regression","display_name":"Bayesian linear regression","score":0.5630614757537842},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5548457503318787},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5539631843566895},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5191454291343689},{"id":"https://openalex.org/keywords/probit-model","display_name":"Probit model","score":0.47043320536613464},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46875810623168945},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4539565443992615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.449916809797287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44489237666130066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4337725043296814},{"id":"https://openalex.org/keywords/multinomial-probit","display_name":"Multinomial probit","score":0.42129766941070557},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4061572551727295},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4013126790523529}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5751469135284424},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.5630614757537842},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5548457503318787},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5539631843566895},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5191454291343689},{"id":"https://openalex.org/C67257552","wikidata":"https://www.wikidata.org/wiki/Q635217","display_name":"Probit model","level":2,"score":0.47043320536613464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46875810623168945},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4539565443992615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.449916809797287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44489237666130066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4337725043296814},{"id":"https://openalex.org/C46704056","wikidata":"https://www.wikidata.org/wiki/Q17086346","display_name":"Multinomial probit","level":3,"score":0.42129766941070557},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4061572551727295},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4013126790523529},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s00180-019-00917-8","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s00180-019-00917-8","pdf_url":null,"source":{"id":"https://openalex.org/S8500805","display_name":"Computational Statistics","issn_l":"0943-4062","issn":["0943-4062","1613-9658"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:compst:v:35:y:2020:i:1:d:10.1007_s00180-019-00917-8","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s00180-019-00917-8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2197740258","display_name":null,"funder_award_id":"11501294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W109881820","https://openalex.org/W1749992802","https://openalex.org/W1982652137","https://openalex.org/W1986825443","https://openalex.org/W1998610098","https://openalex.org/W2007069447","https://openalex.org/W2012551717","https://openalex.org/W2038574031","https://openalex.org/W2056324615","https://openalex.org/W2056760934","https://openalex.org/W2066068511","https://openalex.org/W2083875149","https://openalex.org/W2087684630","https://openalex.org/W2100322632","https://openalex.org/W2108306139","https://openalex.org/W2109363337","https://openalex.org/W2113745932","https://openalex.org/W2114102615","https://openalex.org/W2117135012","https://openalex.org/W2117825844","https://openalex.org/W2123172482","https://openalex.org/W2125056473","https://openalex.org/W2136380442","https://openalex.org/W2143030432","https://openalex.org/W2143426320","https://openalex.org/W2146766088","https://openalex.org/W2152828142","https://openalex.org/W2156332695","https://openalex.org/W2156909104","https://openalex.org/W2157875785","https://openalex.org/W2339195677","https://openalex.org/W2437356612","https://openalex.org/W2481210167","https://openalex.org/W2585809897","https://openalex.org/W2611104316","https://openalex.org/W2750669744","https://openalex.org/W2877844890","https://openalex.org/W2963108610","https://openalex.org/W4298876635"],"related_works":["https://openalex.org/W1988552146","https://openalex.org/W1564853802","https://openalex.org/W2018403506","https://openalex.org/W2077986001","https://openalex.org/W71678127","https://openalex.org/W2157655363","https://openalex.org/W4205763938","https://openalex.org/W2292189132","https://openalex.org/W4288092343","https://openalex.org/W4386114318"],"abstract_inverted_index":null,"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}