{"id":"https://openalex.org/W2962979308","doi":"https://doi.org/10.14736/kyb-2018-4-0765","title":"Gaussian approximation for functionals of Gibbs particle processes","display_name":"Gaussian approximation for functionals of Gibbs particle processes","publication_year":2018,"publication_date":"2018-09-24","ids":{"openalex":"https://openalex.org/W2962979308","doi":"https://doi.org/10.14736/kyb-2018-4-0765","mag":"2962979308"},"language":"en","primary_location":{"id":"doi:10.14736/kyb-2018-4-0765","is_oa":false,"landing_page_url":"https://doi.org/10.14736/kyb-2018-4-0765","pdf_url":null,"source":{"id":"https://openalex.org/S158577884","display_name":"Kybernetika","issn_l":"0023-5954","issn":["0023-5954","1805-949X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314340","host_organization_name":"Institute of Information Theory and Automation of the Czech Academy of Sciences","host_organization_lineage":["https://openalex.org/P4310314340","https://openalex.org/P4310314171"],"host_organization_lineage_names":["Institute of Information Theory and Automation of the Czech Academy of Sciences","Czech Academy of Sciences"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetika","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://dml.cz/bitstream/handle/10338.dmlcz/147423/Kybernetika_54-2018-4_8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081300355","display_name":"Daniela Flimmel","orcid":"https://orcid.org/0000-0001-7847-4482"},"institutions":[{"id":"https://openalex.org/I21250087","display_name":"Charles University","ror":"https://ror.org/024d6js02","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21250087"]},{"id":"https://openalex.org/I4210153325","display_name":"Institute of Mathematical Statistics","ror":"https://ror.org/043f04882","country_code":"US","type":"other","lineage":["https://openalex.org/I4210153325"]}],"countries":["CZ","US"],"is_corresponding":false,"raw_author_name":"Daniela Flimmel","raw_affiliation_strings":["Department of Probability and Mathematical Statistics,","Faculty of Mathematics and Physics, Charles University, Sokolovsk\u00e1 83, 18675 Praha 8, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Probability and Mathematical Statistics,","institution_ids":["https://openalex.org/I4210153325"]},{"raw_affiliation_string":"Faculty of Mathematics and Physics, Charles University, Sokolovsk\u00e1 83, 18675 Praha 8, Czech Republic","institution_ids":["https://openalex.org/I21250087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103126551","display_name":"Viktor Bene\u0161","orcid":"https://orcid.org/0000-0002-7312-9492"},"institutions":[{"id":"https://openalex.org/I21250087","display_name":"Charles University","ror":"https://ror.org/024d6js02","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21250087"]},{"id":"https://openalex.org/I4210153325","display_name":"Institute of Mathematical Statistics","ror":"https://ror.org/043f04882","country_code":"US","type":"other","lineage":["https://openalex.org/I4210153325"]}],"countries":["CZ","US"],"is_corresponding":false,"raw_author_name":"Viktor Bene\u0161","raw_affiliation_strings":["Department of Probability and Mathematical Statistics,","Faculty of Mathematics and Physics, Charles University, Sokolovsk\u00e1 83, 18675 Praha 8, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Probability and Mathematical Statistics,","institution_ids":["https://openalex.org/I4210153325"]},{"raw_affiliation_string":"Faculty of Mathematics and Physics, Charles University, Sokolovsk\u00e1 83, 18675 Praha 8, Czech Republic","institution_ids":["https://openalex.org/I21250087"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2174,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59726624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"765","last_page":"777"},"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":0.9506000280380249,"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":0.9506000280380249,"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/T11830","display_name":"Point processes and geometric inequalities","score":0.9258000254631042,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"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":0.9211999773979187,"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/statistical-physics","display_name":"Statistical physics","score":0.5708792805671692},{"id":"https://openalex.org/keywords/particle","display_name":"Particle (ecology)","score":0.5203437209129333},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5155177116394043},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46357017755508423},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4371544122695923},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.42794108390808105},{"id":"https://openalex.org/keywords/particle-system","display_name":"Particle system","score":0.4107523560523987},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.34808096289634705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3115782141685486},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1476234495639801},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.13766974210739136},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11361527442932129},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09526556730270386}],"concepts":[{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5708792805671692},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.5203437209129333},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5155177116394043},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46357017755508423},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4371544122695923},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.42794108390808105},{"id":"https://openalex.org/C179003449","wikidata":"https://www.wikidata.org/wiki/Q1757458","display_name":"Particle system","level":2,"score":0.4107523560523987},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.34808096289634705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3115782141685486},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1476234495639801},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.13766974210739136},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11361527442932129},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09526556730270386},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14736/kyb-2018-4-0765","is_oa":false,"landing_page_url":"https://doi.org/10.14736/kyb-2018-4-0765","pdf_url":null,"source":{"id":"https://openalex.org/S158577884","display_name":"Kybernetika","issn_l":"0023-5954","issn":["0023-5954","1805-949X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314340","host_organization_name":"Institute of Information Theory and Automation of the Czech Academy of Sciences","host_organization_lineage":["https://openalex.org/P4310314340","https://openalex.org/P4310314171"],"host_organization_lineage_names":["Institute of Information Theory and Automation of the Czech Academy of Sciences","Czech Academy of Sciences"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetika","raw_type":"journal-article"},{"id":"pmh:oai:oai.dml.cz:10338.dmlcz/147423","is_oa":true,"landing_page_url":"http://hdl.handle.net/10338.dmlcz/147423","pdf_url":"http://dml.cz/bitstream/handle/10338.dmlcz/147423/Kybernetika_54-2018-4_8.pdf","source":{"id":"https://openalex.org/S4406922294","display_name":"Czech digital mathematics library","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"type:math"}],"best_oa_location":{"id":"pmh:oai:oai.dml.cz:10338.dmlcz/147423","is_oa":true,"landing_page_url":"http://hdl.handle.net/10338.dmlcz/147423","pdf_url":"http://dml.cz/bitstream/handle/10338.dmlcz/147423/Kybernetika_54-2018-4_8.pdf","source":{"id":"https://openalex.org/S4406922294","display_name":"Czech digital mathematics library","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"type:math"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2588012278","display_name":null,"funder_award_id":"SVV 2017 No. 260454","funder_id":"https://openalex.org/F4320309755","funder_display_name":"Univerzita Karlova v Praze"},{"id":"https://openalex.org/G4169840624","display_name":"Spatial geometrical statistics of random sets in Euclidean spaces","funder_award_id":"GA16-03708S","funder_id":"https://openalex.org/F4320321006","funder_display_name":"Grantov\u00e1 Agentura \u010cesk\u00e9 Republiky"}],"funders":[{"id":"https://openalex.org/F4320309755","display_name":"Univerzita Karlova v Praze","ror":"https://ror.org/024d6js02"},{"id":"https://openalex.org/F4320321006","display_name":"Grantov\u00e1 Agentura \u010cesk\u00e9 Republiky","ror":"https://ror.org/01pv73b02"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962979308.pdf","grobid_xml":"https://content.openalex.org/works/W2962979308.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W565214016","https://openalex.org/W1507653385","https://openalex.org/W2035525102","https://openalex.org/W2037933156","https://openalex.org/W2071313227","https://openalex.org/W2434721019","https://openalex.org/W2611971621","https://openalex.org/W2767091268","https://openalex.org/W2963986696","https://openalex.org/W4233064940","https://openalex.org/W4248312410","https://openalex.org/W4297271037","https://openalex.org/W4297787448","https://openalex.org/W4300213103"],"related_works":["https://openalex.org/W3146360815","https://openalex.org/W1570787356","https://openalex.org/W1863602751","https://openalex.org/W208520381","https://openalex.org/W2989848887","https://openalex.org/W3037216507","https://openalex.org/W4233378595","https://openalex.org/W625004508","https://openalex.org/W2312544580","https://openalex.org/W2043277408"],"abstract_inverted_index":{"summary:In":[0],"the":[1,18,23,30,39,45,48,62,68,74,86],"paper":[2],"asymptotic":[3],"properties":[4],"of":[5,7,32,47,70,88,101],"functionals":[6,100],"stationary":[8,49],"Gibbs":[9,50,75,104],"particle":[10],"processes":[11],"are":[12,27],"derived.":[13],"Two":[14],"known":[15],"techniques":[16],"from":[17],"point":[19,51],"process":[20,52],"theory":[21],"in":[22],"Euclidean":[24],"space":[25,31,87],"$\\mathbb{R}^d$":[26,36],"extended":[28],"to":[29,67,85,94],"compact":[33,89],"sets":[34,90],"on":[35],"equipped":[37],"with":[38,53],"Hausdorff":[40],"metric.":[41],"First,":[42],"conditions":[43],"for":[44,99],"existence":[46],"given":[54],"conditional":[55],"intensity":[56],"have":[57],"been":[58],"simplified":[59],"recently.":[60],"Secondly,":[61],"Malliavin-Stein":[63],"method":[64],"was":[65],"applied":[66],"estimation":[69],"Wasserstein":[71],"distance":[72],"between":[73],"input":[76],"and":[77,91],"standard":[78],"Gaussian":[79,97],"distribution.":[80],"We":[81],"transform":[82],"these":[83],"theories":[84],"use":[92],"them":[93],"derive":[95],"a":[96,102],"approximation":[98],"planar":[103],"segment":[105],"process.":[106]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-30T07:30:35.949966","created_date":"2025-10-10T00:00:00"}