{"id":"https://openalex.org/W48380957","doi":"https://doi.org/10.1007/978-3-642-57489-4_64","title":"Locally Adaptive Function Estimation for Categorical Regression Models","display_name":"Locally Adaptive Function Estimation for Categorical Regression Models","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W48380957","doi":"https://doi.org/10.1007/978-3-642-57489-4_64","mag":"48380957"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-57489-4_64","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-57489-4_64","pdf_url":null,"source":{"id":"https://openalex.org/S4306506691","display_name":"COMPSTAT","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Compstat","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/A5053138997","display_name":"Alexander Jerak","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alexander Jerak","raw_affiliation_strings":["Department of Statistics, University of Munich, Ludwigstr. 33, 80539, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Munich, Ludwigstr. 33, 80539, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085041409","display_name":"Stefan Lang","orcid":"https://orcid.org/0000-0003-0619-0098"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Lang","raw_affiliation_strings":["Department of Statistics, University of Munich, Ludwigstr. 33, 80539, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Munich, Ludwigstr. 33, 80539, Munich, Germany","institution_ids":["https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053138997"],"corresponding_institution_ids":["https://openalex.org/I8204097"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01437341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"425","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9976999759674072,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9976999759674072,"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/categorical-variable","display_name":"Categorical variable","score":0.7964175939559937},{"id":"https://openalex.org/keywords/nonparametric-regression","display_name":"Nonparametric regression","score":0.6729352474212646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6243711709976196},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6139591932296753},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5640600323677063},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4707389771938324},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4428979158401489},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4112265706062317},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3614528179168701},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3453767001628876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3344268202781677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.30475834012031555}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.7964175939559937},{"id":"https://openalex.org/C74127309","wikidata":"https://www.wikidata.org/wiki/Q3455886","display_name":"Nonparametric regression","level":3,"score":0.6729352474212646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6243711709976196},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6139591932296753},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5640600323677063},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4707389771938324},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4428979158401489},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4112265706062317},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3614528179168701},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3453767001628876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3344268202781677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30475834012031555},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-642-57489-4_64","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-57489-4_64","pdf_url":null,"source":{"id":"https://openalex.org/S4306506691","display_name":"COMPSTAT","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Compstat","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1544729927","https://openalex.org/W1912628714","https://openalex.org/W2108306139","https://openalex.org/W2155729182","https://openalex.org/W2158940042"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W2085259108","https://openalex.org/W3041320102","https://openalex.org/W4236247486","https://openalex.org/W1979200279","https://openalex.org/W4253065990"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"present":[4],"a":[5],"nonparametric":[6],"Bayesian":[7,57],"approach":[8,23],"for":[9,32,67],"fitting":[10],"un-smooth":[11],"or":[12,41,51],"highly":[13],"oscillating":[14],"functions":[15,36],"in":[16],"regression":[17,65],"models":[18,66],"with":[19,47],"categorical":[20,64],"responses.":[21,34],"The":[22],"extends":[24],"previous":[25],"work":[26],"by":[27,39],"Lang":[28],"et":[29],"al.":[30],"(2002)":[31],"Gaussian":[33],"Nonlinear":[35],"are":[37],"modelled":[38],"first":[40],"second":[42],"order":[43],"random":[44],"walk":[45],"priors":[46],"locally":[48],"varying":[49],"variances":[50],"smoothing":[52],"parameters.":[53],"Estimation":[54],"is":[55],"fully":[56],"and":[58],"uses":[59],"latent":[60],"utility":[61],"representations":[62],"of":[63,75],"efficient":[68],"block":[69],"sampling":[70],"from":[71],"the":[72],"full":[73],"conditionals":[74],"nonlinear":[76],"functions.":[77]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}