{"id":"https://openalex.org/W7164854565","doi":"https://doi.org/10.48550/arxiv.2606.14532","title":"Modeling inhomogeneous spatial point configurations with applications to replicated patterns in real-life waiting crowds","display_name":"Modeling inhomogeneous spatial point configurations with applications to replicated patterns in real-life waiting crowds","publication_year":2026,"publication_date":"2026-06-12","ids":{"openalex":"https://openalex.org/W7164854565","doi":"https://doi.org/10.48550/arxiv.2606.14532"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2606.14532","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2606.14532","pdf_url":"https://arxiv.org/pdf/2606.14532","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2606.14532","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138688082","display_name":"Lars Sickert Karam","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Karam, Lars Sickert","raw_affiliation_strings":["Department of Mathematics & Computer Science and Eindhoven Artificial Intelligence Systems Institute (EAISI) , Eindhoven University of Technology , Eindhoven , The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics & Computer Science and Eindhoven Artificial Intelligence Systems Institute (EAISI) , Eindhoven University of Technology , Eindhoven , The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101555643","display_name":"Rui M. Castro","orcid":"https://orcid.org/0000-0003-4398-0718","observed_orcids":["https://orcid.org/0000-0003-4398-0718"]},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Castro, Rui M.","raw_affiliation_strings":["Department of Mathematics & Computer Science and Eindhoven Artificial Intelligence Systems Institute (EAISI) , Eindhoven University of Technology , Eindhoven , The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics & Computer Science and Eindhoven Artificial Intelligence Systems Institute (EAISI) , Eindhoven University of Technology , Eindhoven , The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056957450","display_name":"Maarten Schoukens","orcid":"https://orcid.org/0000-0002-4904-1255","observed_orcids":["https://orcid.org/0000-0002-4904-1255"]},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Schoukens, Maarten","raw_affiliation_strings":["Department of Electrical Engineering and EAISI , Eindhoven University of Technology , Eindhoven , The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and EAISI , Eindhoven University of Technology , Eindhoven , The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044502179","display_name":"Alessandro Corbetta","orcid":"https://orcid.org/0000-0001-6979-3414","observed_orcids":["https://orcid.org/0000-0001-6979-3414"]},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Corbetta, Alessandro","raw_affiliation_strings":["Department of Applied Physics & Science Education and EAISI , Eindhoven University of Technology , Eindhoven , The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Physics & Science Education and EAISI , Eindhoven University of Technology , Eindhoven , The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I83019370"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T11830","display_name":"Point processes and geometric inequalities","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9994999766349792,"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10482","display_name":"Mathematical and Theoretical Epidemiology and Ecology Models","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spatial-point-processes","display_name":"spatial point processes","score":0.9120000004768372},{"id":"https://openalex.org/keywords/determinantal-point-processes","display_name":"determinantal point processes","score":0.8809999823570251},{"id":"https://openalex.org/keywords/gibbs-point-processes","display_name":"Gibbs point processes","score":0.9980000257492065},{"id":"https://openalex.org/keywords/spatial-heterogeneity","display_name":"spatial heterogeneity","score":0.7730000019073486},{"id":"https://openalex.org/keywords/repulsive-interactions","display_name":"repulsive interactions","score":0.8640000224113464},{"id":"https://openalex.org/keywords/place-attractiveness","display_name":"location attractiveness","score":0.8980000019073486},{"id":"https://openalex.org/keywords/pedestrian-dynamics","display_name":"pedestrian dynamics","score":0.38600000739097595}],"concepts":[{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.8618999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110000252723694},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.669700026512146},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.45399999618530273},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4530999958515167},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.438400000333786},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C138695830","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial dependence","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.3172000050544739},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3068999946117401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3061000108718872},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C72010251","wikidata":"https://www.wikidata.org/wiki/Q5265688","display_name":"Determinantal point process","level":4,"score":0.2815999984741211},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28139999508857727},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2606.14532","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2606.14532","pdf_url":"https://arxiv.org/pdf/2606.14532","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"doi:10.48550/arxiv.2606.14532","doi":"https://doi.org/10.48550/arxiv.2606.14532","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.14532","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2606.14532","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2606.14532","pdf_url":"https://arxiv.org/pdf/2606.14532","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7164854565.pdf","grobid_xml":"https://content.openalex.org/works/W7164854565.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W7139094457","https://openalex.org/W7221023320"],"related_works":["https://openalex.org/W4244914388","https://openalex.org/W639274387","https://openalex.org/W7125613193","https://openalex.org/W7145281252","https://openalex.org/W4226094421","https://openalex.org/W3210270227","https://openalex.org/W2605127999","https://openalex.org/W7099981707","https://openalex.org/W3188378378","https://openalex.org/W6996760869"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3,27,52],"connect":[4],"statistical":[5],"inference":[6,30,88],"for":[7,32,63],"spatial":[8,34,40,55,70,92,105],"point":[9,35,56,93,110,145],"processes":[10,57,146],"with":[11],"the":[12,24,48,87,126,130,135,161],"analysis":[13],"of":[14,163,176],"waiting":[15,64,177],"pedestrian":[16,121],"crowds":[17],"through":[18,117],"two":[19,67,82],"interconnected":[20],"contributions.":[21],"First,":[22],"on":[23,97],"methodological":[25,127],"side":[26],"develop":[28],"an":[29],"procedure":[31],"semiparametric":[33],"process":[36,94,111],"models":[37,168],"leveraging":[38],"replicated":[39,104],"patterns,":[41],"i.e.,":[42],"multiple":[43],"approximately":[44],"independent":[45],"realizations":[46],"from":[47,101,165],"same":[49],"process.":[50],"Second,":[51],"show":[53],"that":[54],"provide":[58],"a":[59,118,148,152],"suitable":[60],"modeling":[61,95],"framework":[62],"pedestrians,":[65],"capturing":[66],"key":[68,173],"aspects:":[69],"inhomogeneity":[71,164],"driven":[72],"by":[73],"location":[74],"attractiveness":[75],"and":[76,140,143,151],"repulsive":[77],"interactions":[78],"between":[79],"pedestrians.":[80,178],"These":[81],"components":[83],"are":[84,107,114,169],"central":[85],"to":[86,129,138,171],"problem":[89],"itself,":[90],"since":[91],"hinges":[96],"disentangling":[98],"background":[99],"intensity":[100],"interaction.":[102],"Although":[103],"patterns":[106],"rare":[108],"in":[109,147,159],"literature,":[112],"they":[113],"available":[115],"here":[116],"unique":[119],"real-life":[120],"dataset,":[122],"thereby":[123],"directly":[124],"linking":[125],"development":[128],"physical":[131],"application.":[132],"We":[133],"use":[134],"proposed":[136],"methods":[137],"fit":[139],"evaluate":[141],"determinantal":[142],"Gibbs":[144],"simulation":[149],"study":[150],"real-world":[153],"case":[154],"study.":[155],"Despite":[156],"persistent":[157],"challenges":[158],"decoupling":[160],"influences":[162],"interaction,":[166],"these":[167],"able":[170],"reproduce":[172],"empirical":[174],"features":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-06-16T00:00:00"}
