{"id":"https://openalex.org/W2116330964","doi":null,"title":"GIBBS SAMPLING FOR THE UNINITIATED","display_name":"GIBBS SAMPLING FOR THE UNINITIATED","publication_year":2010,"publication_date":"2010-04-16","ids":{"openalex":"https://openalex.org/W2116330964","mag":"2116330964"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.156.2875","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.2875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.umiacs.umd.edu/users/resnik/pubs/gibbs.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/A5059946729","display_name":"Philip Resnik","orcid":"https://orcid.org/0000-0002-6130-8602","observed_orcids":["https://orcid.org/0000-0002-6130-8602"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Resnik","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":"https://orcid.org/0000-0002-6130-8602","affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009183333","display_name":"Eric A. Hardisty","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric A. Hardisty","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":6.1885,"has_fulltext":false,"cited_by_count":84,"citation_normalized_percentile":{"value":0.97280062,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"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":0.9980000257492065,"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":0.9980000257492065,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.001500000013038516,"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":9.999999747378752e-05,"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/gibbs-sampling","display_name":"Gibbs sampling","score":1.0},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.9789999723434448},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.9900000095367432},{"id":"https://openalex.org/keywords/naive-bayes-model","display_name":"naive Bayes model","score":0.7749999761581421},{"id":"https://openalex.org/keywords/text-processing","display_name":"text processing","score":0.9750000238418579}],"concepts":[{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.848823070526123},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7697231769561768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6063256859779358},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.531491756439209},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.5092067122459412},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4864823520183563},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.47578537464141846},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.45726239681243896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3859962821006775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3482697010040283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2661091089248657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2498161494731903},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08177495002746582},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.156.2875","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.2875","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.umiacs.umd.edu/users/resnik/pubs/gibbs.pdf","raw_type":"text"},{"id":"pmh:oai:drum.lib.umd.edu:1903/10058","doi":null,"is_oa":false,"landing_page_url":"https://drum.lib.umd.edu/bitstream/1903/10058/3/gsfu.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"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":"Technical Report"},{"id":"mag:2116330964","doi":null,"is_oa":false,"landing_page_url":"https://apps.dtic.mil/sti/pdfs/ADA523027.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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W114565888","https://openalex.org/W195465510","https://openalex.org/W1546863579","https://openalex.org/W1574901103","https://openalex.org/W1663973292","https://openalex.org/W1840759059","https://openalex.org/W2032175749","https://openalex.org/W2091797506","https://openalex.org/W2109233187","https://openalex.org/W2110591510","https://openalex.org/W2111668269","https://openalex.org/W2135194391","https://openalex.org/W2140213100","https://openalex.org/W2149537132","https://openalex.org/W2159080219","https://openalex.org/W2164151151","https://openalex.org/W2169470026","https://openalex.org/W3140968660"],"related_works":["https://openalex.org/W7098069914","https://openalex.org/W2017899835","https://openalex.org/W1580681286","https://openalex.org/W7098978986","https://openalex.org/W2294136611","https://openalex.org/W2258778752","https://openalex.org/W7100030004","https://openalex.org/W7039193880","https://openalex.org/W4236586296","https://openalex.org/W1619437807"],"abstract_inverted_index":{"This":[0],"document":[1],"is":[2],"intended":[3],"for":[4,108],"computer":[5],"scientists":[6],"who":[7],"would":[8],"like":[9],"to":[10,23,32,37,40,66,137,142,147],"try":[11,36],"out":[12,126],"a":[13,105,109],"Markov":[14],"Chain":[15],"Monte":[16],"Carlo":[17],"(MCMC)":[18],"technique,":[19],"particularly":[20],"in":[21,59,70,90,101],"order":[22],"do":[24],"inference":[25],"with":[26,114,134],"Bayesian":[27],"models":[28],"on":[29],"problems":[30],"related":[31],"text":[33],"processing.":[34],"We":[35,132],"keep":[38],"theory":[39],"the":[41,49,77,91,115,124],"absolute":[42],"minimum":[43],"needed,":[44],"though":[45],"we":[46,95,117],"work":[47,96],"through":[48,97],"details":[50],"much":[51],"more":[52,145],"explicitly":[53],"than":[54],"you":[55],"usually":[56],"see":[57],"even":[58],"\"introductory\"":[60],"explanations.":[61],"That":[62],"means":[63],"we've":[64,140],"attempted":[65],"be":[67,143],"ridiculously":[68],"explicit":[69],"our":[71,88],"exposition":[72],"and":[73,79],"notation.":[74],"After":[75],"providing":[76],"reasons":[78],"reasoning":[80],"behind":[81],"Gibbs":[82,106],"sampling":[83],"(and":[84],"at":[85],"least":[86],"nodding":[87],"heads":[89],"direction":[92],"of":[93,104,127],"theory),":[94],"an":[98],"example":[99],"application":[100],"detail|the":[102],"derivation":[103],"sampler":[107],"Naive":[110],"Bayes":[111],"model.":[112],"Along":[113],"example,":[116],"discuss":[118],"some":[119,135],"practical":[120],"implementation":[121],"issues,":[122],"including":[123],"integrating":[125],"continuous":[128],"parameters":[129],"when":[130],"possible.":[131],"conclude":[133],"pointers":[136],"literature":[138],"that":[139],"found":[141],"somewhat":[144],"friendly":[146],"uninitiated":[148],"readers.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}