{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T13:05:18Z","timestamp":1751634318368,"version":"3.37.3"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,6,4]],"date-time":"2022-06-04T00:00:00Z","timestamp":1654300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,6,4]],"date-time":"2022-06-04T00:00:00Z","timestamp":1654300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100011871","name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011871","name":"Pontificia Universidad Cat\u00f3lica del Per\u00fa","doi-asserted-by":"publisher","award":["DGI-000000000000740"],"award-info":[{"award-number":["DGI-000000000000740"]}],"id":[{"id":"10.13039\/501100011871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Conselho Nacional de Pesquisa e Desenvolvimento","award":["436948\/2018-4","PQ- 307457\/2018-4"],"award-info":[{"award-number":["436948\/2018-4","PQ- 307457\/2018-4"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Comput Stat"],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s00180-022-01235-2","type":"journal-article","created":{"date-parts":[[2022,6,4]],"date-time":"2022-06-04T10:02:31Z","timestamp":1654336951000},"page":"603-621","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima\u2013Peru"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9289-386X","authenticated-orcid":false,"given":"Carlos","family":"Garc\u00eda","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zaida","family":"Quiroz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcos","family":"Prates","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,4]]},"reference":[{"key":"1235_CR1","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780199689491.003.0010","volume-title":"Some regression models for AF measures, chap 10","author":"S Alkire","year":"2015","unstructured":"Alkire S, Foster J, Seth S, Santos M, Roche J, Ballon P (2015) Some regression models for AF measures, chap 10. Oxford University Press, Oxford. https:\/\/doi.org\/10.1093\/acprof:oso\/9780199689491.003.0010"},{"issue":"3","key":"1235_CR2","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1353\/jda.2014.0046","volume":"48","author":"E Alvi","year":"2014","unstructured":"Alvi E, Senbeta A (2014) Foreign aid, growth, and poverty relation: a quantile regression approach. J Dev Areas 48(3):381\u2013403","journal-title":"J Dev Areas"},{"key":"1235_CR3","unstructured":"Assun\u00e7\u00e3o G (2018) Regress\u00e3o espacial quant\u00edlica para previs\u00e3o da velocidade do vento. Dissertation, Departamento de Estatistica, Universidade Federal de Minas Gerais, Minas Gerais, Brazil"},{"issue":"3","key":"1235_CR4","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1007\/s13253-021-00451-5","volume":"26","author":"DRM Azevedo","year":"2021","unstructured":"Azevedo DRM, Prates MO, Bandyopadhyay D (2021) Alleviating spatial confounding in multivariate disease mapping models. J Agric Biol Environ Stat 26(3):464\u2013491","journal-title":"J Agric Biol Environ Stat"},{"key":"1235_CR5","doi-asserted-by":"publisher","DOI":"10.1201\/b17115","volume-title":"Hierarchical modeling and analysis for spatial data","author":"S Banerjee","year":"2014","unstructured":"Banerjee S, Carlin B, Gelfand A (2014) Hierarchical modeling and analysis for spatial data. Chapman and Hall\/CRC, New York"},{"key":"1235_CR6","doi-asserted-by":"publisher","first-page":"483","DOI":"10.4310\/SII.2017.v10.n3.a11","volume":"10","author":"C Bayes","year":"2017","unstructured":"Bayes C, Baz\u00e1n J, Castro M (2017) A quantile parametric mixed regression model for bounded response variables. Stat Interface 10:483\u2013493","journal-title":"Stat Interface"},{"issue":"2","key":"1235_CR7","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1111\/j.2517-6161.1974.tb00999.x","volume":"36","author":"J Besag","year":"1974","unstructured":"Besag J (1974) Spatial interaction and the statistical analysis of lattice systems. J R Stat Soc B 36(2):192\u2013236","journal-title":"J R Stat Soc B"},{"issue":"1","key":"1235_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BF00116466","volume":"43","author":"J Besag","year":"1991","unstructured":"Besag J, York J, Molli\u00e9 A (1991) Bayesian image restoration, with two applications in spatial statistics. Ann Inst Stat Math 43(1):1\u201320","journal-title":"Ann Inst Stat Math"},{"key":"1235_CR9","first-page":"224","volume":"4","author":"A Camargo","year":"2011","unstructured":"Camargo A, Hurtado Tarazona A (2011) Vivienda y pobreza: una relaci\u00f3n compleja. marco conceptual y caracterizaci\u00f3n de Bogot\u00e1. Cuad Vivienda Urban 4:224\u2013246","journal-title":"Cuad Vivienda Urban"},{"key":"1235_CR10","doi-asserted-by":"publisher","DOI":"10.1186\/s40488-017-0073-4","author":"P Congdon","year":"2017","unstructured":"Congdon P (2017) Quantile regression for overdispersed count data: a hierarchical method. J Stat Distrib Appl. https:\/\/doi.org\/10.1186\/s40488-017-0073-4","journal-title":"J Stat Distrib Appl"},{"key":"1235_CR11","doi-asserted-by":"publisher","unstructured":"Dupont E, Wood Wood SN, Augustin N (2022) Spatial+: a novel approach to spatial confounding. Biometrics. https:\/\/doi.org\/10.1111\/biom.13656(accepted)","DOI":"10.1111\/biom.13656"},{"issue":"2","key":"1235_CR12","doi-asserted-by":"publisher","first-page":"95","DOI":"10.4310\/20-SII617","volume":"14","author":"SE Flores","year":"2020","unstructured":"Flores SE, Prates MO, Baz\u00e1n JL, Bolfarine HB (2020) Spatial regression models for bounded response variables with evaluation of the degree of dependence. Stat Interface 14(2):95\u2013107","journal-title":"Stat Interface"},{"issue":"3","key":"1235_CR13","doi-asserted-by":"publisher","first-page":"761","DOI":"10.2307\/1913475","volume":"52","author":"J Foster","year":"1984","unstructured":"Foster J, Greer J, Thorbecke E (1984) A class of decomposable poverty measures. Econometrica 52(3):761\u2013766","journal-title":"Econometrica"},{"key":"1235_CR14","doi-asserted-by":"crossref","unstructured":"Geweke J (1992) Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. In: Bayesian statistics, vol\u00a04. Clarendon Press, Oxford, pp 169\u2013193","DOI":"10.21034\/sr.148"},{"issue":"1","key":"1235_CR15","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1080\/09709274.2015.11906856","volume":"50","author":"F Habyarimana","year":"2015","unstructured":"Habyarimana F, Zewotir T, Ramroop S (2015) Determinants of poverty of households in Rwanda: an application of quantile regression. J Hum Ecol 50(1):19\u201330. https:\/\/doi.org\/10.1080\/09709274.2015.11906856","journal-title":"J Hum Ecol"},{"issue":"1","key":"1235_CR16","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1007\/s13253-016-0274-1","volume":"22","author":"TJ Hefley","year":"2017","unstructured":"Hefley TJ, Hooten MB, Hanks EM, Russell RE, Walsh DP (2017) The Bayesian group Lasso for confounded spatial data. J Agric Biol Environ Stat 22(1):42\u201359","journal-title":"J Agric Biol Environ Stat"},{"key":"1235_CR17","first-page":"1593","volume":"15","author":"M Hoffman","year":"2011","unstructured":"Hoffman M, Gelman A (2011) The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. J Mach Learn Res 15:1593\u20131623","journal-title":"J Mach Learn Res"},{"issue":"1","key":"1235_CR18","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1111\/j.1467-9868.2012.01041.x","volume":"75","author":"J Hughes","year":"2013","unstructured":"Hughes J, Haran M (2013) Dimension reduction and alleviation of confounding for spatial generalized linear mixed models. J R Stat Soc B 75(1):139\u2013159","journal-title":"J R Stat Soc B"},{"issue":"4","key":"1235_CR19","doi-asserted-by":"publisher","first-page":"950","DOI":"10.1111\/j.1541-0420.2005.00359.x","volume":"61","author":"X Jin","year":"2005","unstructured":"Jin X, Carlin BP, Banerjee S (2005) Generalized hierarchical multivariate CAR models for areal data. Biometrics 61(4):950\u2013961","journal-title":"Biometrics"},{"key":"1235_CR20","doi-asserted-by":"publisher","unstructured":"Keeley B (2015) How does income inequality affect our lives? In: Income inequality: the gap between rich and poor. OECD Insights, Paris. https:\/\/doi.org\/10.1787\/9789264246010-en","DOI":"10.1787\/9789264246010-en"},{"issue":"1,2","key":"1235_CR21","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/0022-1694(80)90036-0","volume":"46","author":"P Kumaraswamy","year":"1980","unstructured":"Kumaraswamy P (1980) A generalized probability density function for double-bounded random processes. J Hydrol 46(1,2):79\u201388","journal-title":"J Hydrol"},{"key":"1235_CR22","doi-asserted-by":"crossref","unstructured":"Leroux BG, Lei X, Breslow N (2000) Estimation of disease rates in small areas: a new mixed model for spatial dependence. In: Statistical models in epidemiology, the environment, and clinical trials, vol 116. Springer, New York, pp 179\u2013191","DOI":"10.1007\/978-1-4612-1284-3_4"},{"key":"1235_CR23","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s00362-011-0417-y","volume":"54","author":"PA Mitnik","year":"2013","unstructured":"Mitnik PA, Baek S (2013) The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation. Stat Pap 54:177\u2013192. https:\/\/doi.org\/10.1007\/s00362-011-0417-y","journal-title":"Stat Pap"},{"key":"1235_CR24","unstructured":"Ortiz\u00a0Mart\u00ednez JdC (2006) Fecundidad y pobreza en el Per\u00fa: 1996, 2000 y 2004. Technical report, Centro de Investigaci\u00f3n y Desarrollo del Instituto Nacional de Estad\u00edstica e Inform\u00e1tica (INEI), Lima, Per\u00fa. https:\/\/www.inei.gob.pe\/media\/MenuRecursivo\/publicaciones_digitales\/Est\/Lib0688\/Libro.pdf"},{"key":"1235_CR25","doi-asserted-by":"publisher","unstructured":"Padellini T, Rue H (2019) Model-aware quantile regression for discrete data. https:\/\/doi.org\/10.48550\/arXiv.1804.03714. arXiv:1804.03714(unpublished)","DOI":"10.48550\/arXiv.1804.03714"},{"issue":"3","key":"1235_CR26","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1111\/rssa.12551","volume":"183","author":"JB Pereira","year":"2020","unstructured":"Pereira JB, Nobre WS, Silva IF, Schmidt AM (2020) Spatial confounding in hurdle multilevel beta models: the case of the Brazilian mathematical olympics for public schools. J R Stat Soc A Stat Soc 183(3):1051\u20131073","journal-title":"J R Stat Soc A Stat Soc"},{"issue":"2","key":"1235_CR27","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1214\/18-BA1123","volume":"14","author":"MO Prates","year":"2019","unstructured":"Prates MO, Assun\u00e7\u00e3o RM, Rodrigues EC (2019) Alleviating spatial confounding for areal data problems by displacing the geographical centroids. Bayesian Anal 14(2):623\u2013647. https:\/\/doi.org\/10.1214\/18-BA1123","journal-title":"Bayesian Anal"},{"issue":"1","key":"1235_CR28","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1353\/jda.2013.0001","volume":"47","author":"MA Rahman","year":"2013","unstructured":"Rahman MA (2013) Household characteristics and poverty: a logistic regression analysis. J Dev Areas 47(1):303\u2013317","journal-title":"J Dev Areas"},{"issue":"493","key":"1235_CR29","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1198\/jasa.2010.ap09237","volume":"106","author":"B Reich","year":"2011","unstructured":"Reich B, Fuentes M, Dunson D (2011) Bayesian spatial quantile regression. J Am Stat Assoc 106(493):6\u201320","journal-title":"J Am Stat Assoc"},{"issue":"4","key":"1235_CR30","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1111\/j.1541-0420.2006.00617.x","volume":"62","author":"BJ Reich","year":"2006","unstructured":"Reich BJ, Hodges JS, Zadnik V (2006) Effects of residual smoothing on the posterior of the fixed effects in disease-mapping models. Biometrics 62(4):1197\u20131206","journal-title":"Biometrics"},{"key":"1235_CR31","unstructured":"Stan Development Team (2021) Stan modeling language users guide and reference manual, 2.28.0. http:\/\/mc-stan.org\/"},{"issue":"3","key":"1235_CR32","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1080\/00031305.2017.1305290","volume":"72","author":"H Thaden","year":"2018","unstructured":"Thaden H, Kneib T (2018) Structural equation models for dealing with spatial confounding. Am Stat 72(3):239\u2013252","journal-title":"Am Stat"}],"container-title":["Computational Statistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-022-01235-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00180-022-01235-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-022-01235-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T12:50:06Z","timestamp":1727355006000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00180-022-01235-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,4]]},"references-count":32,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["1235"],"URL":"https:\/\/doi.org\/10.1007\/s00180-022-01235-2","relation":{},"ISSN":["0943-4062","1613-9658"],"issn-type":[{"type":"print","value":"0943-4062"},{"type":"electronic","value":"1613-9658"}],"subject":[],"published":{"date-parts":[[2022,6,4]]},"assertion":[{"value":"29 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 June 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}