{"id":"https://openalex.org/W2037516052","doi":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","title":"Bayesian estimation of semi-parametric non-stationary spatial covariance structures","display_name":"Bayesian estimation of semi-parametric non-stationary spatial covariance structures","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W2037516052","doi":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","mag":"2037516052"},"language":"en","primary_location":{"id":"doi:10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","doi":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","is_oa":false,"landing_page_url":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","pdf_url":null,"source":{"id":"https://openalex.org/S17114410","display_name":"Environmetrics","issn_l":"1099-095X","issn":["1099-095X","1180-4009"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Environmetrics","raw_type":"journal-article"},"volume":null,"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/A5104533563","display_name":"Doris Damian","orcid":"https://orcid.org/0000-0002-9562-9746","observed_orcids":["https://orcid.org/0000-0002-9562-9746"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Doris Damian","raw_affiliation_strings":["Department of Biostatistics and NRCSE, University of Washington, Seattle, WA, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics and NRCSE, University of Washington, Seattle, WA, U.S.A","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048311948","display_name":"Paul D. Sampson","orcid":"https://orcid.org/0000-0003-2018-4225","observed_orcids":["https://orcid.org/0000-0003-2018-4225"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul D Sampson","raw_affiliation_strings":["Department of Statistics and NRCSE, University of Washington, Seattle, WA, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and NRCSE, University of Washington, Seattle, WA, U.S.A","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006979328","display_name":"Peter M. Guttorp","orcid":"https://orcid.org/0000-0002-5620-4200","observed_orcids":["https://orcid.org/0000-0002-5620-4200"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Guttorp","raw_affiliation_strings":["Department of Statistics and NRCSE, University of Washington, Seattle, WA, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and NRCSE, University of Washington, Seattle, WA, U.S.A","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5104533563"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":{"value":4780,"currency":"USD","value_usd":4780},"apc_paid":null,"fwci":15.4071,"has_fulltext":false,"cited_by_count":115,"citation_normalized_percentile":{"value":0.98570416,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"2","first_page":"161","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9721999764442444,"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"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9721999764442444,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.016599999740719795,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spatial-correlation-function","display_name":"spatial correlation function","score":0.7910000085830688},{"id":"https://openalex.org/keywords/space-deformation","display_name":"space deformation","score":0.8330000042915344},{"id":"https://openalex.org/keywords/bayesian-estimation","display_name":"Bayesian estimation","score":0.8299999833106995},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7170000076293945},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"uncertainty quantification","score":0.8059999942779541},{"id":"https://openalex.org/keywords/spatial-interpolation","display_name":"spatial interpolation","score":0.3400000035762787}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5777326822280884},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.5747427940368652},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5533984899520874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5327883362770081},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5129629969596863},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5064598321914673},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46402671933174133},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4463483691215515},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4257497787475586},{"id":"https://openalex.org/C53622274","wikidata":"https://www.wikidata.org/wiki/Q2496679","display_name":"Correlation function (quantum field theory)","level":3,"score":0.41456714272499084},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41051048040390015},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37402522563934326},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3616842031478882},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3476322889328003},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1695336401462555},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.09794965386390686},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","doi":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","is_oa":false,"landing_page_url":"https://doi.org/10.1002/1099-095x(200103)12:2<161::aid-env452>3.0.co;2-g","pdf_url":null,"source":{"id":"https://openalex.org/S17114410","display_name":"Environmetrics","issn_l":"1099-095X","issn":["1099-095X","1180-4009"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-c","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Environmetrics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306107","display_name":"U.S. Environmental Protection Agency","ror":"https://ror.org/03tns0030"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2040850257","https://openalex.org/W1656369909","https://openalex.org/W1964627159","https://openalex.org/W2504393198","https://openalex.org/W4401512017","https://openalex.org/W3173598035","https://openalex.org/W219711488","https://openalex.org/W2088028068","https://openalex.org/W28467821","https://openalex.org/W3110960533"],"abstract_inverted_index":{"We":[0,149],"use":[1],"the":[2,9,29,32,55,58,75,78,95,98,102,126,144],"Sampson":[3],"and":[4,101,157],"Guttorp":[5],"approach":[6,110],"to":[7,49,77,116,161],"model":[8],"non-stationary":[10],"correlation":[11,34,99],"function":[12,35,100],"r(x,":[13,41],"x\u2032)":[14,42],"of":[15,61,64,81,97,107,119,121,130,147],"a":[16,21,50,62,84,131,154,162],"Gaussian":[17],"spatial":[18,33],"process":[19],"through":[20,153],"bijective":[22],"space":[23,31,60,128],"deformation,":[24],"f,":[25],"so":[26],"that":[27,112],"in":[28,57],"deformed":[30,59],"can":[36],"be":[37],"considered":[38],"isotropic,":[39],"namely":[40],"=":[43],"\u03c1(\u2223":[44],"f(x)\u2212f(x\u2032)\u2223),":[45],"where":[46],"\u03c1":[47],"belongs":[48],"known":[51],"parametric":[52],"family.":[53],"Given":[54],"locations":[56],"number":[63],"geographic":[65],"sites":[66],"at":[67],"which":[68],"data":[69,164],"are":[70],"available,":[71],"we":[72,87,135],"smoothly":[73],"extrapolate":[74],"deformation":[76],"whole":[79],"region":[80],"interest.":[82,148],"Using":[83],"Bayesian":[85,109],"framework,":[86],"estimate":[88],"jointly":[89],"these":[90,123],"locations,":[91],"as":[92,94],"well":[93],"parameters":[96],"variance":[103],"parameters.":[104,124],"The":[105],"advantage":[106],"our":[108,151],"is":[111,129],"it":[113],"allows":[114],"us":[115],"obtain":[117],"measures":[118],"uncertainty":[120],"all":[122],"As":[125],"parameter":[127],"very":[132],"high":[133],"dimension,":[134],"implement":[136],"an":[137,159],"MCMC":[138],"method":[139,152],"for":[140],"obtaining":[141],"samples":[142],"from":[143],"posterior":[145],"distributions":[146],"demonstrate":[150],"simulation":[155],"study,":[156],"show":[158],"application":[160],"real":[163],"set.":[165],"Copyright":[166],"\u00a9":[167],"2001":[168],"John":[169],"Wiley":[170],"&":[171],"Sons,":[172],"Ltd.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":5}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2016-06-24T00:00:00"}