{"id":"https://openalex.org/W1489119587","doi":"https://doi.org/10.1007/978-94-011-5014-9_7","title":"Introduction to Monte Carlo Methods","display_name":"Introduction to Monte Carlo Methods","publication_year":1998,"publication_date":"1998-01-01","ids":{"openalex":"https://openalex.org/W1489119587","doi":"https://doi.org/10.1007/978-94-011-5014-9_7","mag":"1489119587"},"language":"en","primary_location":{"id":"doi:10.1007/978-94-011-5014-9_7","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-94-011-5014-9_7","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Learning in Graphical Models","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/A5053054196","display_name":"David Mackay","orcid":"https://orcid.org/0000-0002-5271-2996"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210096386","display_name":"Bridge University","ror":"https://ror.org/00cbm0437","country_code":"SS","type":"education","lineage":["https://openalex.org/I4210096386"]}],"countries":["GB","SS"],"is_corresponding":true,"raw_author_name":"D. J. C. Mackay","raw_affiliation_strings":["Department of Physics, Cavendish Laboratory, Cambridge University, Madingley Road, Cambridge, CB3 0HE, UK","CAMBRIDGE UNIVERSITY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics, Cavendish Laboratory, Cambridge University, Madingley Road, Cambridge, CB3 0HE, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"CAMBRIDGE UNIVERSITY","institution_ids":["https://openalex.org/I4210096386"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053054196"],"corresponding_institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210096386"],"apc_list":null,"apc_paid":null,"fwci":13.3117,"has_fulltext":false,"cited_by_count":580,"citation_normalized_percentile":{"value":0.9894871,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9991000294685364,"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":0.9991000294685364,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9988999962806702,"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/T11152","display_name":"Stochastic processes and statistical mechanics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7840796709060669},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.7011914253234863},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"Rejection sampling","score":0.6579289436340332},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6162407398223877},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.5929815173149109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5392609238624573},{"id":"https://openalex.org/keywords/metropolis\u2013hastings-algorithm","display_name":"Metropolis\u2013Hastings algorithm","score":0.496982604265213},{"id":"https://openalex.org/keywords/monte-carlo-integration","display_name":"Monte Carlo integration","score":0.49000588059425354},{"id":"https://openalex.org/keywords/monte-carlo-method-in-statistical-physics","display_name":"Monte Carlo method in statistical physics","score":0.47191646695137024},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.349107027053833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27772659063339233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18791788816452026},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14810240268707275},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.08693492412567139},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0598166286945343}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7840796709060669},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.7011914253234863},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.6579289436340332},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6162407398223877},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.5929815173149109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5392609238624573},{"id":"https://openalex.org/C204693719","wikidata":"https://www.wikidata.org/wiki/Q910810","display_name":"Metropolis\u2013Hastings algorithm","level":4,"score":0.496982604265213},{"id":"https://openalex.org/C132725507","wikidata":"https://www.wikidata.org/wiki/Q39879","display_name":"Monte Carlo integration","level":5,"score":0.49000588059425354},{"id":"https://openalex.org/C204493344","wikidata":"https://www.wikidata.org/wiki/Q6904698","display_name":"Monte Carlo method in statistical physics","level":5,"score":0.47191646695137024},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.349107027053833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27772659063339233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18791788816452026},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14810240268707275},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.08693492412567139},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0598166286945343}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-94-011-5014-9_7","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-94-011-5014-9_7","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Learning in Graphical Models","raw_type":"book-chapter"},{"id":"pmh:oai:generic.eprints.org:91546","is_oa":false,"landing_page_url":"http://publications.eng.cam.ac.uk/91546/","pdf_url":null,"source":{"id":"https://openalex.org/S4406922847","display_name":"Cambridge University Engineering Department Publications Database","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.375.7581","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.375.7581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/~motionplanning/papers/sbp_papers/kalman/intro_montecarlo.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W1977671418","https://openalex.org/W1983628095","https://openalex.org/W2001795831","https://openalex.org/W2033900415","https://openalex.org/W2102862543","https://openalex.org/W2106706098","https://openalex.org/W2204383650","https://openalex.org/W2950733338","https://openalex.org/W4229929111","https://openalex.org/W4388395091"],"related_works":["https://openalex.org/W2539839227","https://openalex.org/W2023579776","https://openalex.org/W4250051631","https://openalex.org/W2108207895","https://openalex.org/W2914481316","https://openalex.org/W2081255987","https://openalex.org/W4367155567","https://openalex.org/W13281851","https://openalex.org/W4294529948","https://openalex.org/W2045761178"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":23},{"year":2016,"cited_by_count":35},{"year":2015,"cited_by_count":28},{"year":2014,"cited_by_count":21},{"year":2013,"cited_by_count":24},{"year":2012,"cited_by_count":25}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
