{"id":"https://openalex.org/W4387709626","doi":"https://doi.org/10.1016/j.csda.2023.107875","title":"Integrating machine learning and Bayesian nonparametrics for flexible modeling of point pattern data","display_name":"Integrating machine learning and Bayesian nonparametrics for flexible modeling of point pattern data","publication_year":2023,"publication_date":"2023-10-17","ids":{"openalex":"https://openalex.org/W4387709626","doi":"https://doi.org/10.1016/j.csda.2023.107875"},"language":"en","primary_location":{"id":"doi:10.1016/j.csda.2023.107875","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.csda.2023.107875","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics &amp; Data Analysis","raw_type":"journal-article"},"type":"article","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/A5005838379","display_name":"Matthew J. Heaton","orcid":"https://orcid.org/0000-0003-4654-9827"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Matthew J. Heaton","raw_affiliation_strings":["Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093077974","display_name":"Benjamin K. Dahl","orcid":"https://orcid.org/0009-0008-2502-2210"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin K. Dahl","raw_affiliation_strings":["Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093077975","display_name":"Caleb Dayley","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caleb Dayley","raw_affiliation_strings":["Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085226414","display_name":"Richard L. Warr","orcid":"https://orcid.org/0000-0001-8508-3105"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard L. Warr","raw_affiliation_strings":["Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054803811","display_name":"Philip A. White","orcid":"https://orcid.org/0000-0003-0907-9221"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip White","raw_affiliation_strings":["Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Brigham Young University, 2152 WVB, Provo, UT, 84602, USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5005838379"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":{"value":3340,"currency":"USD","value_usd":3340},"apc_paid":null,"fwci":0.1737,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57614548,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"191","issue":null,"first_page":"107875","last_page":"107875"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9926999807357788,"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":0.9926999807357788,"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/T11830","display_name":"Point processes and geometric inequalities","score":0.9803000092506409,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9638000130653381,"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/covariate","display_name":"Covariate","score":0.8446294069290161},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6199228167533875},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5837329626083374},{"id":"https://openalex.org/keywords/cox-process","display_name":"Cox process","score":0.5808782577514648},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.5777408480644226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4985809326171875},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4963892102241516},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44946011900901794},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4286883473396301},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.410671591758728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4043358564376831},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3902954161167145},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38120630383491516},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3743898868560791},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3089215159416199},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2667926549911499},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.19648435711860657},{"id":"https://openalex.org/keywords/poisson-process","display_name":"Poisson process","score":0.0939863920211792}],"concepts":[{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.8446294069290161},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6199228167533875},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5837329626083374},{"id":"https://openalex.org/C155051063","wikidata":"https://www.wikidata.org/wiki/Q1290919","display_name":"Cox process","level":4,"score":0.5808782577514648},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.5777408480644226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4985809326171875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4963892102241516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44946011900901794},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4286883473396301},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.410671591758728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4043358564376831},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3902954161167145},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38120630383491516},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3743898868560791},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3089215159416199},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2667926549911499},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.19648435711860657},{"id":"https://openalex.org/C166144826","wikidata":"https://www.wikidata.org/wiki/Q1145117","display_name":"Poisson process","level":3,"score":0.0939863920211792},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.csda.2023.107875","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.csda.2023.107875","pdf_url":null,"source":{"id":"https://openalex.org/S132362803","display_name":"Computational Statistics & Data Analysis","issn_l":"0167-9473","issn":["0167-9473","1872-7352"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Statistics &amp; Data Analysis","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:eee:csdana:v:191:y:2024:i:c:s016794732300186x","is_oa":false,"landing_page_url":"http://www.sciencedirect.com/science/article/pii/S016794732300186X","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8964631056","display_name":null,"funder_award_id":"2053188","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1586180564","https://openalex.org/W1818484123","https://openalex.org/W1966730755","https://openalex.org/W1978537100","https://openalex.org/W1979288019","https://openalex.org/W1981694977","https://openalex.org/W1981890344","https://openalex.org/W1995780830","https://openalex.org/W2011515496","https://openalex.org/W2023708446","https://openalex.org/W2025720061","https://openalex.org/W2033512586","https://openalex.org/W2041722960","https://openalex.org/W2080972498","https://openalex.org/W2091797506","https://openalex.org/W2148534890","https://openalex.org/W2162487434","https://openalex.org/W2190230032","https://openalex.org/W2525528836","https://openalex.org/W2606185014","https://openalex.org/W2613020357","https://openalex.org/W2664410355","https://openalex.org/W2799211855","https://openalex.org/W2920056159","https://openalex.org/W2963622973","https://openalex.org/W2964135075","https://openalex.org/W2971086559","https://openalex.org/W3098932795","https://openalex.org/W3126291162","https://openalex.org/W3176444087","https://openalex.org/W4214740783","https://openalex.org/W6682704874","https://openalex.org/W6687079321","https://openalex.org/W6729793092"],"related_works":["https://openalex.org/W4293193429","https://openalex.org/W4308847323","https://openalex.org/W4225648594","https://openalex.org/W3199062958","https://openalex.org/W2834438054","https://openalex.org/W4289762942","https://openalex.org/W2225046392","https://openalex.org/W2903983794","https://openalex.org/W2093189287","https://openalex.org/W2964260590"],"abstract_inverted_index":null,"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
