{"id":"https://openalex.org/W2501367609","doi":"https://doi.org/10.1007/978-3-319-41920-6_19","title":"Automatic Detection of Latent Common Clusters of Groups in MultiGroup Regression","display_name":"Automatic Detection of Latent Common Clusters of Groups in MultiGroup Regression","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2501367609","doi":"https://doi.org/10.1007/978-3-319-41920-6_19","mag":"2501367609"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-41920-6_19","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-41920-6_19","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5066727281","display_name":"Minhazul Islam Sk","orcid":null},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Minhazul Islam Sk","raw_affiliation_strings":["University of Florida, Gainesville, Florida, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014376423","display_name":"Arunava Banerjee","orcid":"https://orcid.org/0000-0001-9381-4940"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arunava Banerjee","raw_affiliation_strings":["University of Florida, Gainesville, Florida, USA"],"affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066727281"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1326247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"251","last_page":"266"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998999834060669,"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":0.9998999834060669,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9884999990463257,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9865000247955322,"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/generalized-linear-model","display_name":"Generalized linear model","score":0.7691307067871094},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4718256890773773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47102221846580505},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.4541267454624176},{"id":"https://openalex.org/keywords/generalized-linear-mixed-model","display_name":"Generalized linear mixed model","score":0.44522541761398315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44303956627845764},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4116540253162384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34729301929473877},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.34621095657348633}],"concepts":[{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.7691307067871094},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4718256890773773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47102221846580505},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.4541267454624176},{"id":"https://openalex.org/C153720581","wikidata":"https://www.wikidata.org/wiki/Q5532490","display_name":"Generalized linear mixed model","level":2,"score":0.44522541761398315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44303956627845764},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4116540253162384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34729301929473877},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34621095657348633}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-41920-6_19","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-41920-6_19","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"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":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W130710483","https://openalex.org/W987144911","https://openalex.org/W1503100111","https://openalex.org/W1967687583","https://openalex.org/W2014581807","https://openalex.org/W2059191087","https://openalex.org/W2067273358","https://openalex.org/W2069429561","https://openalex.org/W2073626204","https://openalex.org/W2080972498","https://openalex.org/W2091797506","https://openalex.org/W2127498532","https://openalex.org/W2130903752","https://openalex.org/W2131479143","https://openalex.org/W2136979193","https://openalex.org/W2148522164","https://openalex.org/W2148578256","https://openalex.org/W2151967501","https://openalex.org/W2162888803","https://openalex.org/W2509991828","https://openalex.org/W2610550445","https://openalex.org/W2801490189","https://openalex.org/W2913340405","https://openalex.org/W3104240813","https://openalex.org/W3122943284","https://openalex.org/W4237152466","https://openalex.org/W4239390603","https://openalex.org/W4285719527","https://openalex.org/W4292691288"],"related_works":["https://openalex.org/W3081465059","https://openalex.org/W1556631438","https://openalex.org/W1510072949","https://openalex.org/W2356286374","https://openalex.org/W49891529","https://openalex.org/W225107685","https://openalex.org/W4242077822","https://openalex.org/W2132137727","https://openalex.org/W1969243170","https://openalex.org/W2290516599"],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}