{"id":"https://openalex.org/W4281725693","doi":"https://doi.org/10.1080/03610918.2022.2075388","title":"Adaptive cluster path sampling","display_name":"Adaptive cluster path sampling","publication_year":2022,"publication_date":"2022-05-27","ids":{"openalex":"https://openalex.org/W4281725693","doi":"https://doi.org/10.1080/03610918.2022.2075388"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2022.2075388","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2075388","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","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/A5017891178","display_name":"Mena Lao","orcid":null},"institutions":[{"id":"https://openalex.org/I198105771","display_name":"Kasetsart University","ror":"https://ror.org/05gzceg21","country_code":"TH","type":"education","lineage":["https://openalex.org/I198105771"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Mena Lao","raw_affiliation_strings":["Department of Statistics, Faculty of Science, Kasetsart University, Bangkok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Faculty of Science, Kasetsart University, Bangkok, Thailand","institution_ids":["https://openalex.org/I198105771"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016812715","display_name":"Arthur L. Dryver","orcid":null},"institutions":[{"id":"https://openalex.org/I159665162","display_name":"National Institute of Development Administration","ror":"https://ror.org/010g30191","country_code":"TH","type":"education","lineage":["https://openalex.org/I159665162"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Arthur Dryver","raw_affiliation_strings":["School of Business Administration, NIDA, Bangkok, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Business Administration, NIDA, Bangkok, Thailand","institution_ids":["https://openalex.org/I159665162"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017891178"],"corresponding_institution_ids":["https://openalex.org/I198105771"],"apc_list":null,"apc_paid":null,"fwci":0.2328,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54147338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"53","issue":"5","first_page":"2316","last_page":"2329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.9998000264167786,"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/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.9998000264167786,"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/sampling","display_name":"Sampling (signal processing)","score":0.5414798855781555},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5301467180252075},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5291818976402283},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.4984006881713867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47642621397972107},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27695900201797485},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27174627780914307},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12004193663597107},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11618220806121826},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.07647386193275452}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5414798855781555},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5301467180252075},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5291818976402283},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.4984006881713867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47642621397972107},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27695900201797485},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27174627780914307},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12004193663597107},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11618220806121826},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.07647386193275452},{"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":1,"locations":[{"id":"doi:10.1080/03610918.2022.2075388","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2022.2075388","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1989227970","https://openalex.org/W2019343919","https://openalex.org/W2021303792","https://openalex.org/W2029685080","https://openalex.org/W2057725660","https://openalex.org/W2092322680","https://openalex.org/W2141308243","https://openalex.org/W2498260651","https://openalex.org/W2912846719","https://openalex.org/W4233471163"],"related_works":["https://openalex.org/W2038693912","https://openalex.org/W1991602789","https://openalex.org/W1582396021","https://openalex.org/W1988359706","https://openalex.org/W312558119","https://openalex.org/W4210985407","https://openalex.org/W2335441444","https://openalex.org/W138014004","https://openalex.org/W2075598034","https://openalex.org/W1829869244"],"abstract_inverted_index":{"Path":[0,28],"sampling":[1,7,18,29,33,42,56,69,78,83,111,123,130,149,155,159,162],"is":[2,30,37,64,150,164],"one":[3],"of":[4,17,48,61,94,107],"the":[5,15,40,49,59,95,137,141],"economical":[6],"designs":[8],"for":[9],"spatial":[10],"populations":[11],"since":[12],"it":[13,36],"provides":[14,44],"capability":[16],"all":[19],"units":[20],"along":[21],"a":[22,26,31,67,116],"path":[23,74,82,110,122,126,148,154],"traveled":[24],"during":[25],"survey.":[27],"non-adaptive":[32],"design;":[34],"however":[35],"known":[38],"that":[39],"adaptive":[41,77,108,120,128,146,157],"design":[43,70],"more":[45,88,151],"precise":[46,89],"estimates":[47],"population":[50,96],"mean":[51,97,100],"and":[52,80,98,131,156],"total":[53],"than":[54,153],"conventional":[55,81,125],"designs.":[57],"Therefore,":[58],"objective":[60],"this":[62],"article":[63],"to":[65,86,124,136],"propose":[66],"new":[68],"called":[71],"\u201cadaptive":[72],"cluster":[73,109,121,129,147,158],"sampling\u201d":[75],"using":[76],"strategy":[79],"in":[84],"order":[85],"obtain":[87],"parameter":[90],"estimate.":[91],"Two":[92],"estimators":[93],"their":[99],"square":[101],"error":[102],"were":[103],"obtained.":[104],"The":[105],"efficiency":[106],"was":[112],"examined":[113],"by":[114],"performing":[115],"simulation":[117,138],"study,":[118],"comparing":[119],"sampling,":[127],"simple":[132],"random":[133],"sampling.":[134],"According":[135],"results":[139],"on":[140],"blue":[142],"winged":[143],"teal":[144],"data,":[145],"efficient":[152],"when":[160],"equal":[161],"cost":[163],"considered.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}