{"id":"https://openalex.org/W2120030881","doi":"https://doi.org/10.1109/igarss.2012.6351120","title":"Spatially penalized regression for dependence analysis of rare events: A study in precipitation extremes","display_name":"Spatially penalized regression for dependence analysis of rare events: A study in precipitation extremes","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2120030881","doi":"https://doi.org/10.1109/igarss.2012.6351120","mag":"2120030881"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2012.6351120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6351120","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5047008738","display_name":"Debasish Das","orcid":"https://orcid.org/0000-0002-2020-1497"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debasish Das","raw_affiliation_strings":["Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064658255","display_name":"Auroop R. Ganguly","orcid":"https://orcid.org/0000-0002-4292-4856"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Auroop Ganguly","raw_affiliation_strings":["Civil and Environmental Engineering, Northeastern University, Boston, MA, USA","Civil and Environmental Engineering, Northeastern University, Boston MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil and Environmental Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Civil and Environmental Engineering, Northeastern University, Boston MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046920838","display_name":"Snigdhansu Chatterjee","orcid":"https://orcid.org/0000-0002-7986-0470"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Snigdhansu Chatterjee","raw_affiliation_strings":["School of Statistics, University of Minnesota, Minneapolis, MN, USA","School of Statistics, University of Minnesota, Minneapolis, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Statistics, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"School of Statistics, University of Minnesota, Minneapolis, USA#TAB#","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100645812","display_name":"Vipin Kumar","orcid":"https://orcid.org/0000-0002-9040-2665"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vipin Kumar","raw_affiliation_strings":["Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","Computer Science and Eng, University of Minnesota, Minneapolis, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"Computer Science and Eng, University of Minnesota, Minneapolis, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044038055","display_name":"Zoran Obradovi\u0107","orcid":"https://orcid.org/0000-0002-2051-0142"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zoran Obradovic","raw_affiliation_strings":["Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Analytics and Biomedical Informatics, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1948","last_page":"1951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9905999898910522,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9833999872207642,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.8545001745223999},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7269580364227295},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.47644737362861633},{"id":"https://openalex.org/keywords/predictive-power","display_name":"Predictive power","score":0.4686205983161926},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44661208987236023},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.42757993936538696},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4253070652484894},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.40216371417045593},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32787591218948364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2800893783569336},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24270221590995789},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22545641660690308},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1773577630519867},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.15932133793830872},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10965535044670105}],"concepts":[{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.8545001745223999},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7269580364227295},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.47644737362861633},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.4686205983161926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44661208987236023},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.42757993936538696},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4253070652484894},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.40216371417045593},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32787591218948364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2800893783569336},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24270221590995789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22545641660690308},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1773577630519867},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.15932133793830872},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10965535044670105},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/igarss.2012.6351120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6351120","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:doi:10.13016/m2chy3-uwei","is_oa":false,"landing_page_url":"https://doi.org/10.1109/IGARSS.2012.6351120.","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"Text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.352.2675","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.2675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.dabi.temple.edu/~zoran/papers/IGARSS_Paper.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1973039273","https://openalex.org/W2005785499","https://openalex.org/W2063978378","https://openalex.org/W2067715694","https://openalex.org/W2074401196","https://openalex.org/W2074682976","https://openalex.org/W2080273417","https://openalex.org/W2083127256","https://openalex.org/W2083859420","https://openalex.org/W2097360283","https://openalex.org/W2120618726","https://openalex.org/W2122825543","https://openalex.org/W2125716633","https://openalex.org/W2131957523","https://openalex.org/W2135046866","https://openalex.org/W2173251738","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"Discovery":[0],"of":[1,28,37,46,56,77,136,160,184,201],"dependence":[2,92,117,188],"structure":[3,93,118],"between":[4,94,134],"precipitation":[5,96,147],"extremes":[6,38,97],"and":[7,16,98,108,146,157,190,193,209,223],"other":[8],"climate":[9],"variables":[10],"(covariates)":[11],"within":[12,105],"a":[13,74],"smaller":[14],"spatial":[15],"temporal":[17],"neighborhood":[18,76,107,185],"is":[19,50],"an":[20],"important":[21],"step":[22],"in":[23],"better":[24],"understanding":[25],"the":[26,42,47,54,57,91,95,99,137,162,166,195,199,202,224,228,232],"drivers":[27],"this":[29,106,116],"complex":[30],"phenomenon":[31],"as":[32,34],"well":[33],"short-term":[35],"prediction":[36],"occurrence.":[39],"Apart":[40],"from":[41],"inherent":[43],"spatio-temporal":[44,75],"variability":[45],"dependence,":[48],"it":[49,110],"further":[51],"complicated":[52],"by":[53],"availability":[55],"covariates":[58,100,138],"at":[59,194],"different":[60,71,86,88],"vertical":[61],"levels.":[62],"The":[63],"above":[64],"problem":[65],"can":[66,84,119],"be":[67,81,85,103,113,120],"split":[68],"into":[69,165,231],"three":[70,182],"sub-problems.":[72],"Firstly,":[73],"influence":[78],"has":[79,101,111],"to":[80,102,112,226],"discovered,":[82],"which":[83,179],"for":[87,122,154,212],"locations.":[89],"Secondly,":[90],"discovered":[104,130],"thirdly,":[109],"investigated":[114],"whether":[115],"exploited":[121],"any":[123,158],"predictive":[124,191],"power.":[125],"Climate":[126],"scientists":[127],"have":[128],"already":[129],"some":[131,135,213],"physics-based":[132,163,229],"relations":[133,164],"(e.g.":[139],"temperature,":[140],"relative":[141],"humidity,":[142],"precipitable":[143],"water":[144],"etc.)":[145],"extremes.":[148],"We":[149,217],"are":[150,218],"exploring":[151,220],"data-dependent":[152],"alternatives":[153,225],"these":[155],"problems":[156,183],"possibility":[159],"incorporating":[161],"resulting":[167,203],"data":[168,233],"model.":[169,204,234],"In":[170],"particular,":[171],"we":[172],"used":[173],"elastic":[174],"net-based":[175],"sparse":[176],"optimization":[177],"technique":[178],"solves":[180],"all":[181],"discovery,":[186],"covariate":[187],"discovery":[189],"modeling":[192],"same":[196],"time":[197],"maintains":[198],"interpretability":[200],"Preliminary":[205],"results":[206],"look":[207],"promising":[208],"show":[210],"potential":[211],"interesting":[214],"knowledge":[215],"discovery.":[216],"currently":[219],"non-linear":[221],"correlations":[222],"combine":[227],"relationships":[230]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}