{"id":"https://openalex.org/W105487563","doi":null,"title":"Nonparametric Density Estimation via Diffusion Mixing","display_name":"Nonparametric Density Estimation via Diffusion Mixing","publication_year":2007,"publication_date":"2007-11-20","ids":{"openalex":"https://openalex.org/W105487563","mag":"105487563"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.336.5896","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.336.5896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://espace.library.uq.edu.au/eserv/UQ:120006/diffusion_estimator.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5003450294","display_name":"Zdravko I. Botev","orcid":"https://orcid.org/0000-0001-9054-3452","observed_orcids":["https://orcid.org/0000-0001-9054-3452"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zdravko I. Botev","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9054-3452","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5003450294"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0332,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91586786,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.5346999764442444,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.5346999764442444,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.34619998931884766,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.03999999910593033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/nonparametric-density-estimation","display_name":"nonparametric density estimation","score":0.9940000176429749},{"id":"https://openalex.org/keywords/diffusion-mixing","display_name":"diffusion mixing","score":0.7950000166893005},{"id":"https://openalex.org/keywords/langevin-diffusion","display_name":"Langevin diffusion","score":0.8899999856948853},{"id":"https://openalex.org/keywords/prior-information","display_name":"prior information","score":0.6079999804496765},{"id":"https://openalex.org/keywords/non-bayesian-estimation","display_name":"non-Bayesian estimation","score":0.9169999957084656},{"id":"https://openalex.org/keywords/asymptotic-bias","display_name":"asymptotic bias","score":0.7889999747276306},{"id":"https://openalex.org/keywords/asymptotic-variance","display_name":"asymptotic variance","score":0.984000027179718},{"id":"https://openalex.org/keywords/stationary-distribution","display_name":"stationary distribution","score":0.7509999871253967},{"id":"https://openalex.org/keywords/prior-density","display_name":"prior density","score":0.4560000002384186}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8251904249191284},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.6561981439590454},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5702656507492065},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.537590503692627},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.4940691292285919},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.44982096552848816},{"id":"https://openalex.org/C65778772","wikidata":"https://www.wikidata.org/wiki/Q12345341","display_name":"Asymptotic distribution","level":3,"score":0.44026243686676025},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42649373412132263},{"id":"https://openalex.org/C84894716","wikidata":"https://www.wikidata.org/wiki/Q6935135","display_name":"Multivariate kernel density estimation","level":5,"score":0.4253350496292114},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.41826385259628296},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4018714129924774},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3527916669845581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30071690678596497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15758398175239563},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.07747441530227661},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.0},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.336.5896","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.336.5896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://espace.library.uq.edu.au/eserv/UQ:120006/diffusion_estimator.pdf","raw_type":"text"},{"id":"mag:105487563","doi":null,"is_oa":false,"landing_page_url":"https://espace.library.uq.edu.au/view/UQ:120006/diffusion_estimator.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1489950266","https://openalex.org/W1543120048","https://openalex.org/W1984499217","https://openalex.org/W2089349283","https://openalex.org/W2132685693","https://openalex.org/W2139346812","https://openalex.org/W2148745705"],"related_works":["https://openalex.org/W2061150271","https://openalex.org/W2097114126","https://openalex.org/W1783846287","https://openalex.org/W7096679534","https://openalex.org/W2290276022","https://openalex.org/W7098184143","https://openalex.org/W3103587541","https://openalex.org/W7098453565","https://openalex.org/W1489890253","https://openalex.org/W2050189467"],"abstract_inverted_index":{"Suppose":[0],"we":[1],"are":[2],"given":[3],"empirical":[4,58],"data":[5,59],"and":[6,78,89,95],"a":[7,20,47,61],"prior":[8,27,39,51,73],"density":[9,22,43,52,74,104],"about":[10],"the":[11,14,26,36,42,56,72,76,82,86,93,99,102,112,116],"distribution":[12,80],"of":[13,38,81,92,101,122],"data.":[15],"We":[16,29,84,106],"wish":[17],"to":[18],"construct":[19],"nonparametric":[21],"estimator":[23,32,94,114],"that":[24,33,71],"incorporates":[25],"information.":[28],"propose":[30],"an":[31],"allows":[34],"for":[35],"incorporation":[37],"information":[40],"in":[41,110,120],"estimation":[44,118],"procedure":[45],"within":[46],"non-Bayesian":[48],"framework.":[49],"The":[50,65],"is":[53,68,75],"mixed":[54],"with":[55,98],"available":[57],"via":[60],"Langevin":[62],"diffusion":[63,66],"process.":[64,83],"process":[67],"constructed":[69],"so":[70],"limiting":[77],"stationary":[79],"analyze":[85],"asymptotic":[87],"bias":[88],"variance":[90],"properties":[91,100],"compare":[96],"them":[97],"standard":[103,117],"estimators.":[105],"present":[107],"simulation":[108],"examples":[109],"which":[111],"proposed":[113],"outperforms":[115],"procedures":[119],"terms":[121],"accuracy.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2016-06-24T00:00:00"}
