{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T16:40:27Z","timestamp":1740588027640,"version":"3.38.0"},"reference-count":91,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T00:00:00Z","timestamp":1740009600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T00:00:00Z","timestamp":1740009600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["PJT-148774"],"award-info":[{"award-number":["PJT-148774"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["1R35GM150537-01"],"award-info":[{"award-number":["1R35GM150537-01"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2019-04810"],"award-info":[{"award-number":["RGPIN-2019-04810"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Stat Comput"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s11222-025-10582-1","type":"journal-article","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T13:27:41Z","timestamp":1740058061000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Using prior-data conflict to tune Bayesian regularized regression models"],"prefix":"10.1007","volume":"35","author":[{"given":"Timofei","family":"Biziaev","sequence":"first","affiliation":[]},{"given":"Karen","family":"Kopciuk","sequence":"additional","affiliation":[]},{"given":"Thierry","family":"Chekouo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,20]]},"reference":[{"key":"10582_CR1","doi-asserted-by":"crossref","unstructured":"Akaike, H.: Information theory and an extension of the maximum likelihood principle. In: Selected papers of Hirotugu Akaike, pp. 199\u2013213. Springer (1998)","DOI":"10.1007\/978-1-4612-1694-0_15"},{"issue":"1","key":"10582_CR2","first-page":"119","volume":"23","author":"A Armagan","year":"2013","unstructured":"Armagan, A., Dunson, D.B., Lee, J.: Generalized double Pareto shrinkage. Stat. Sin. 23(1), 119 (2013)","journal-title":"Stat. Sin."},{"issue":"4","key":"10582_CR3","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1007\/s11222-010-9182-3","volume":"21","author":"YF Atchad\u00e9","year":"2011","unstructured":"Atchad\u00e9, Y.F.: A computational framework for empirical Bayes inference. Stat. Comput. 21(4), 463\u2013473 (2011)","journal-title":"Stat. Comput."},{"key":"10582_CR4","volume-title":"Handbook of bayesian variable selection","author":"R Bai","year":"2021","unstructured":"Bai, R., Ro\u010dkov\u00e1, V., George, E.I.: Spike-and-slab meets lasso: a review of the spike-and-slab lasso. In: Tadesse, M.G., Vannucci, M. (eds.) Handbook of bayesian variable selection. CRC Press, Boca Raton, FL (2021)"},{"issue":"3","key":"10582_CR5","first-page":"870","volume":"2","author":"MM Barbieri","year":"2004","unstructured":"Barbieri, M.M., Berger, J.O.: Optimal predictive model selection. Ann. Stat. 2(3), 870\u2013897 (2004)","journal-title":"Ann. Stat."},{"key":"10582_CR6","doi-asserted-by":"crossref","unstructured":"Baskurt, Z., Evans, M.: Hypothesis assessment and inequalities for bayes factors and relative belief ratios (2013)","DOI":"10.1214\/13-BA824"},{"issue":"2","key":"10582_CR7","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1214\/07-AOS587","volume":"37","author":"JO Berger","year":"2009","unstructured":"Berger, J.O., Bernardo, J.M., Sun, D.: The formal definition of reference priors. Ann. Stat. 37(2), 905\u2013938 (2009)","journal-title":"Ann. Stat."},{"issue":"433","key":"10582_CR8","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1080\/01621459.1996.10476668","volume":"91","author":"JO Berger","year":"1996","unstructured":"Berger, J.O., Pericchi, L.R.: The intrinsic Bayes factor for model selection and prediction. J. Am. Stat. Assoc. 91(433), 109\u2013122 (1996)","journal-title":"J. Am. Stat. Assoc."},{"issue":"3","key":"10582_CR9","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1214\/19-STS700","volume":"34","author":"A Bhadra","year":"2019","unstructured":"Bhadra, A., Datta, J., Polson, N.G., Willard, B.: Lasso meets horseshoe. Stat. Sci. 34(3), 405\u2013427 (2019)","journal-title":"Stat. Sci."},{"issue":"512","key":"10582_CR10","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.1080\/01621459.2014.960967","volume":"110","author":"A Bhattacharya","year":"2015","unstructured":"Bhattacharya, A., Pati, D., Pillai, N.S., Dunson, D.B.: Dirichlet-Laplace priors for optimal shrinkage. J. Am. Stat. Assoc. 110(512), 1479\u20131490 (2015)","journal-title":"J. Am. Stat. Assoc."},{"issue":"2","key":"10582_CR11","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1111\/j.1541-0420.2011.01680.x","volume":"68","author":"S Biswas","year":"2012","unstructured":"Biswas, S., Lin, S.: Logistic Bayesian LASSO for identifying association with rare haplotypes and application to age-related macular degeneration. Biometrics 68(2), 587\u2013597 (2012)","journal-title":"Biometrics"},{"issue":"9","key":"10582_CR12","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1080\/02664760802192981","volume":"35","author":"N Bousquet","year":"2008","unstructured":"Bousquet, N.: Diagnostics of prior-data agreement in applied Bayesian analysis. J. Appl. Stat. 35(9), 1011\u20131029 (2008)","journal-title":"J. Appl. Stat."},{"key":"10582_CR13","doi-asserted-by":"crossref","unstructured":"Camli, O., Kalaylioglu, Z., SenGupta, A.: Variable selection in linear-circular regression models. J. Appl. Stat., 1\u201322 (2022)","DOI":"10.1080\/02664763.2022.2110860"},{"issue":"2","key":"10582_CR14","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1093\/biomet\/asq017","volume":"97","author":"CM Carvalho","year":"2010","unstructured":"Carvalho, C.M., Polson, N.G., Scott, J.G.: The horseshoe prior for sparse signals. Biometrika 97(2), 465\u2013480 (2010)","journal-title":"Biometrika"},{"issue":"4","key":"10582_CR15","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1038\/s41577-021-00522-1","volume":"21","author":"T Carvalho","year":"2021","unstructured":"Carvalho, T., Krammer, F., Iwasaki, A.: The first 12 months of COVID-19: a timeline of immunological insights. Nat. Rev. Immunol. 21(4), 245\u2013256 (2021)","journal-title":"Nat. Rev. Immunol."},{"issue":"4","key":"10582_CR16","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1093\/biostatistics\/2.4.485","volume":"2","author":"G Casella","year":"2001","unstructured":"Casella, G.: Empirical Bayes Gibbs sampling. Biostatistics 2(4), 485\u2013500 (2001)","journal-title":"Biostatistics"},{"issue":"2","key":"10582_CR17","doi-asserted-by":"crossref","first-page":"3953","DOI":"10.1214\/18-EJS1494","volume":"12","author":"I Castillo","year":"2018","unstructured":"Castillo, I., Mismer, R.: Empirical Bayes analysis of spike and slab posterior distributions. Electron. J. Stat. 12(2), 3953\u20134001 (2018)","journal-title":"Electron. J. Stat."},{"issue":"5","key":"10582_CR18","doi-asserted-by":"crossref","first-page":"1986","DOI":"10.1214\/15-AOS1334","volume":"43","author":"I Castillo","year":"2015","unstructured":"Castillo, I., Schmidt-Hieber, J., van der Vaart, A.: Bayesian linear regression with sparse priors. Ann. Stat. 43(5), 1986\u20132018 (2015)","journal-title":"Ann. Stat."},{"issue":"1","key":"10582_CR19","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1093\/biostatistics\/kxab016","volume":"24","author":"T Chekouo","year":"2022","unstructured":"Chekouo, T., Safo, S.E.: Bayesian integrative analysis and prediction with application to atherosclerosis cardiovascular disease. Biostatistics 24(1), 124\u2013139 (2022)","journal-title":"Biostatistics"},{"issue":"2","key":"10582_CR20","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1111\/biom.12266","volume":"71","author":"T Chekouo","year":"2015","unstructured":"Chekouo, T., Stingo, F.C., Doecke, J.D., Do, K.-A.: miRNA-target gene regulatory networks: a Bayesian integrative approach to biomarker selection with application to kidney cancer. Biometrics 71(2), 428\u2013438 (2015)","journal-title":"Biometrics"},{"issue":"3","key":"10582_CR21","doi-asserted-by":"crossref","first-page":"1547","DOI":"10.1214\/16-AOAS948","volume":"10","author":"T Chekouo","year":"2016","unstructured":"Chekouo, T., Stingo, F.C., Guindani, M., Do, K.-A.: A bayesian predictive model for imaging genetics with application to schizophrenia. The Ann. Appl. Stat. 10(3), 1547\u20131571 (2016)","journal-title":"The Ann. Appl. Stat."},{"issue":"1","key":"10582_CR22","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1080\/24709360.2017.1396742","volume":"1","author":"Y-C Chen","year":"2017","unstructured":"Chen, Y.-C.: A tutorial on kernel density estimation and recent advances. Biostat. Epidemiol. 1(1), 161\u2013187 (2017)","journal-title":"Biostat. Epidemiol."},{"key":"10582_CR23","doi-asserted-by":"crossref","unstructured":"Chipman, H., George, E.\u00a0I., McCulloch, R.\u00a0E., Clyde, M., Foster, D.\u00a0P., Stine, R.\u00a0A.: The practical implementation of Bayesian model selection. Lecture Notes-Monograph Series, 65\u2013134 (2001)","DOI":"10.1214\/lnms\/1215540964"},{"issue":"4","key":"10582_CR24","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1016\/j.jspi.2007.02.011","volume":"138","author":"W Cui","year":"2008","unstructured":"Cui, W., George, E.I.: Empirical Bayes vs. fully Bayes variable selection. J. Stat. Plann. Inference 138(4), 888\u2013900 (2008)","journal-title":"J. Stat. Plann. Inference"},{"key":"10582_CR25","unstructured":"Donoho, D.L., et al.: High-dimensional data analysis: The curses and blessings of dimensionality. AMS math challenges lecture 1(2000), 32 (2000)"},{"issue":"2","key":"10582_CR26","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1002\/cjs.11637","volume":"50","author":"L Egidi","year":"2022","unstructured":"Egidi, L., Pauli, F., Torelli, N.: Avoiding prior-data conflict in regression models via mixture priors. Can. J. Stat. 50(2), 491\u2013510 (2022)","journal-title":"Can. J. Stat."},{"key":"10582_CR27","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.csbj.2015.12.001","volume":"14","author":"M Evans","year":"2016","unstructured":"Evans, M.: Measuring statistical evidence using relative belief. Comput. Struct. Biotechnol. J. 14, 91\u201396 (2016)","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"3","key":"10582_CR28","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1214\/11-STS357","volume":"26","author":"M Evans","year":"2011","unstructured":"Evans, M., Jang, G.H.: Weak informativity and the information in one prior relative to another. Stat. Sci. 26(3), 423\u2013439 (2011)","journal-title":"Stat. Sci."},{"issue":"4","key":"10582_CR29","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1214\/06-BA129","volume":"1","author":"M Evans","year":"2006","unstructured":"Evans, M., Moshonov, H.: Checking for prior-data conflict. Bayesian Anal. 1(4), 893\u2013914 (2006)","journal-title":"Bayesian Anal."},{"key":"10582_CR30","unstructured":"Evans, M., Tomal, J.: Multiple testing via relative belief ratios (2016)"},{"issue":"6","key":"10582_CR31","first-page":"2605","volume":"36","author":"J Fan","year":"2008","unstructured":"Fan, J., Fan, Y.: High dimensional classification using features annealed independence rules. Ann. Stat. 36(6), 2605 (2008)","journal-title":"Ann. Stat."},{"issue":"456","key":"10582_CR32","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1198\/016214501753382273","volume":"96","author":"J Fan","year":"2001","unstructured":"Fan, J., Li, R.: Variable selection via nonconcave penalized likelihood and its oracle properties. J. Am. Stat. Assoc. 96(456), 1348\u20131360 (2001)","journal-title":"J. Am. Stat. Assoc."},{"key":"10582_CR33","unstructured":"Fan, J., Li, R.: Statistical challenges with high dimensionality: feature selection in knowledge discovery. arXiv preprint arXiv:math\/0602133 (2006)"},{"issue":"1","key":"10582_CR34","first-page":"101","volume":"20","author":"J Fan","year":"2010","unstructured":"Fan, J., Lv, J.: A selective overview of variable selection in high dimensional feature space. Stat. Sin. 20(1), 101 (2010)","journal-title":"Stat. Sin."},{"issue":"2","key":"10582_CR35","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/S0304-4076(00)00076-2","volume":"100","author":"C Fernandez","year":"2001","unstructured":"Fernandez, C., Ley, E., Steel, M.F.: Benchmark priors for Bayesian model averaging. J. Econ. 100(2), 381\u2013427 (2001)","journal-title":"J. Econ."},{"issue":"3","key":"10582_CR36","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1214\/06-BA117A","volume":"1","author":"A Gelman","year":"2006","unstructured":"Gelman, A.: Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1(3), 515\u2013534 (2006)","journal-title":"Bayesian Anal."},{"key":"10582_CR37","doi-asserted-by":"crossref","unstructured":"Gelman, A., Carlin, J.\u00a0B., Stern, H.\u00a0S., Rubin, D.\u00a0B.: Bayesian data analysis. Chapman and Hall\/CRC (1995)","DOI":"10.1201\/9780429258411"},{"issue":"4","key":"10582_CR38","first-page":"457","volume":"7","author":"A Gelman","year":"1992","unstructured":"Gelman, A., Rubin, D.B.: Inference from iterative simulation using multiple sequences. Stat. Sci. 7(4), 457\u2013472 (1992)","journal-title":"Stat. Sci."},{"issue":"4","key":"10582_CR39","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/j.anai.2016.07.038","volume":"117","author":"KT Gemayel","year":"2016","unstructured":"Gemayel, K.T., Litman, G.W., Sriaroon, P.: Autosomal recessive agammaglobulinemia associated with an IGLL1 gene missense mutation. Ann. Allergy Asthma Immunol. 117(4), 439\u2013441 (2016)","journal-title":"Ann. Allergy Asthma Immunol."},{"issue":"3","key":"10582_CR40","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1198\/004017007000000245","volume":"49","author":"A Genking","year":"2007","unstructured":"Genking, A., Lewis, D.D., Madigan, D.: Large-scale Bayesian logistic regression for text categorization. Technometrics 49(3), 291\u2013304 (2007)","journal-title":"Technometrics"},{"issue":"4","key":"10582_CR41","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1093\/biomet\/87.4.731","volume":"87","author":"EI George","year":"2000","unstructured":"George, E.I., Foster, D.P.: Calibration and empirical Bayes variable selection. Biometrika 87(4), 731\u2013747 (2000)","journal-title":"Biometrika"},{"issue":"423","key":"10582_CR42","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1080\/01621459.1993.10476353","volume":"88","author":"EI George","year":"1993","unstructured":"George, E.I., McCulloch, R.E.: Variable selection via Gibbs sampling. J. Am. Stat. Assoc. 88(423), 881\u2013889 (1993)","journal-title":"J. Am. Stat. Assoc."},{"issue":"2","key":"10582_CR43","first-page":"339","volume":"7","author":"EI George","year":"1997","unstructured":"George, E.I., McCulloch, R.E.: Approaches for Bayesian variable selection. Stat. Sin. 7(2), 339\u2013373 (1997)","journal-title":"Stat. Sin."},{"issue":"3","key":"10582_CR44","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1214\/15-BA973","volume":"11","author":"P Ghosh","year":"2016","unstructured":"Ghosh, P., Tang, X., Ghosh, M., Chakrabarti, A.: Asymptotic properties of Bayes risk of a general class of shrinkage priors in multiple hypothesis testing under sparsity. Bayesian Anal. 11(3), 753\u2013796 (2016)","journal-title":"Bayesian Anal."},{"key":"10582_CR45","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.ins.2013.06.018","volume":"249","author":"M Gil","year":"2013","unstructured":"Gil, M., Alajaji, F., Linder, T.: R\u00e9nyi divergence measures for commonly used univariate continuous distributions. Inf. Sci. 249, 124\u2013131 (2013)","journal-title":"Inf. Sci."},{"issue":"509","key":"10582_CR46","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1080\/01621459.2014.993077","volume":"110","author":"PR Hahn","year":"2015","unstructured":"Hahn, P.R., Carvalho, C.M.: Decoupling shrinkage and selection in bayesian linear models: a posterior summary perspective. J. Am. Stat. Assoc. 110(509), 435\u2013448 (2015)","journal-title":"J. Am. Stat. Assoc."},{"key":"10582_CR47","doi-asserted-by":"crossref","unstructured":"Harrell, F.: Regression modeling strategies: with applications to linear models, logistic and ordinal regression and survival analysis. (2 ed.). Springer Series in Statistics (2001)","DOI":"10.1007\/978-1-4757-3462-1"},{"issue":"1","key":"10582_CR48","first-page":"1","volume":"14","author":"A Huang","year":"2013","unstructured":"Huang, A., Xu, S., Cai, X.: Empirical Bayesian LASSO-logistic regression for multiple binary trait locus mapping. BMC Genet. 14(1), 1\u201314 (2013)","journal-title":"BMC Genet."},{"issue":"462","key":"10582_CR49","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1198\/016214503000224","volume":"98","author":"H Ishwaran","year":"2003","unstructured":"Ishwaran, H., Rao, J.S.: Detecting differentially expressed genes in microarrays using bayesian model selection. J. Am. Stat. Assoc. 98(462), 438\u2013455 (2003)","journal-title":"J. Am. Stat. Assoc."},{"issue":"430","key":"10582_CR50","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1080\/01621459.1995.10476572","volume":"90","author":"RE Kass","year":"1995","unstructured":"Kass, R.E., Raftery, A.E.: Bayes factors. J. Am. Stat. Assoc. 90(430), 773\u2013795 (1995)","journal-title":"J. Am. Stat. Assoc."},{"issue":"540","key":"10582_CR51","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1080\/01621459.2021.1891926","volume":"117","author":"DR Kowal","year":"2022","unstructured":"Kowal, D.R.: Fast, optimal, and targeted predictions using parameterized decision analysis. J. Am. Stat. Assoc. 117(540), 1875\u20131886 (2022)","journal-title":"J. Am. Stat. Assoc."},{"key":"10582_CR52","unstructured":"Kuo, L., Mallick, B.: Variable selection for regression models. Sankhya: The Indian J. Stat. Series B, 65\u201381 (1998)"},{"issue":"2","key":"10582_CR53","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/s10463-013-0429-6","volume":"66","author":"C Leng","year":"2014","unstructured":"Leng, C., Tran, M.-N., Nott, D.: Bayesian adaptive Lasso. Ann. Inst. Stat. Math. 66(2), 221\u2013244 (2014)","journal-title":"Ann. Inst. Stat. Math."},{"issue":"3","key":"10582_CR54","first-page":"1001","volume":"17","author":"K-C Li","year":"1989","unstructured":"Li, K.-C.: Honest confidence regions for nonparametric regression. Ann. Stat. 17(3), 1001\u20131008 (1989)","journal-title":"Ann. Stat."},{"issue":"1","key":"10582_CR55","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1007\/s00180-021-01115-1","volume":"37","author":"W Li","year":"2022","unstructured":"Li, W., Chekouo, T.: Bayesian group selection with non-local priors. Comput. Stat. 37(1), 287\u2013302 (2022)","journal-title":"Comput. Stat."},{"issue":"4","key":"10582_CR56","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1214\/aoms\/1177728069","volume":"27","author":"DV Lindley","year":"1956","unstructured":"Lindley, D.V.: On a measure of the information provided by an experiment. Ann. Math. Stat. 27(4), 986\u20131005 (1956)","journal-title":"Ann. Math. Stat."},{"issue":"4","key":"10582_CR57","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0267047","volume":"17","author":"D Lipman","year":"2022","unstructured":"Lipman, D., Safo, S.E., Chekouo, T.: Multi-omic analysis reveals enriched pathways associated with COVID-19 and COVID-19 severity. PLoS ONE 17(4), e0267047 (2022)","journal-title":"PLoS ONE"},{"key":"10582_CR58","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s11222-012-9316-x","volume":"23","author":"A Lykou","year":"2013","unstructured":"Lykou, A., Ntzoufras, I.: On bayesian lasso variable selection and the specification of the shrinkage parameter. Stat. Comput. 23, 361\u2013390 (2013)","journal-title":"Stat. Comput."},{"key":"10582_CR59","first-page":"870","volume":"32","author":"M Maddalena","year":"2004","unstructured":"Maddalena, M., Berger, J.O.: Optimal predictive model selection. Ann. Stat. 32, 870\u2013897 (2004)","journal-title":"Ann. Stat."},{"key":"10582_CR60","unstructured":"Malsiner-Walli, G., Wagner, H.: Comparing spike and slab priors for bayesian variable selection. arXiv preprintarXiv:1812.07259 (2018)"},{"issue":"488","key":"10582_CR61","doi-asserted-by":"crossref","first-page":"1671","DOI":"10.1198\/jasa.2009.tm08647","volume":"104","author":"N Meinshausen","year":"2009","unstructured":"Meinshausen, N., Meier, L., B\u00fchlmann, P.: P-values for high-dimensional regression. J. Am. Stat. Assoc. 104(488), 1671\u20131681 (2009)","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"10582_CR62","first-page":"208","volume":"1","author":"C Myles","year":"2008","unstructured":"Myles, C., Wayne, M.: Quantitative trait locus (QTL) analysis. Nat. Educ. 1(1), 208 (2008)","journal-title":"Nat. Educ."},{"issue":"2","key":"10582_CR63","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1214\/14-AOS1207","volume":"42","author":"NN Narisetty","year":"2014","unstructured":"Narisetty, N.N., Hel, X.: Bayesian variable selection with shrinking and diffusing priors. Ann. Stat. 42(2), 789\u2013817 (2014)","journal-title":"Ann. Stat."},{"issue":"1","key":"10582_CR64","first-page":"203","volume":"16","author":"DJ Nott","year":"2021","unstructured":"Nott, D.J., Seah, M., Al-Labadi, L., Evans, M., Ng, H.K., Englert, B.-G.: Using Prior Expansions for Prior-Data Conflict Checking. Bayesian Anal. 16(1), 203\u2013231 (2021)","journal-title":"Bayesian Anal."},{"issue":"2","key":"10582_CR65","first-page":"243","volume":"35","author":"DJ Nott","year":"2020","unstructured":"Nott, D.J., Wang, X., Evans, M., Englert, B.-G.: Checking for Prior-Data Conflict using prior-to-posterior divergences. Stat. Sci. 35(2), 243\u2013253 (2020)","journal-title":"Stat. Sci."},{"issue":"4","key":"10582_CR66","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1016\/j.jmva.2006.10.001","volume":"98","author":"DJ Nott","year":"2007","unstructured":"Nott, D.J., Yu, Z., Chan, E., Cotsapas, C., Cowley, M.J., Pulvers, J., Williams, R., Little, P.: Hierarchical Bayes variable selection and microarray experiments. J. Multivar. Anal. 98(4), 852\u2013872 (2007)","journal-title":"J. Multivar. Anal."},{"key":"10582_CR67","doi-asserted-by":"crossref","unstructured":"O\u2019hara, R.B., Sillanp\u00e4\u00e4, M.J.: A review of Bayesian variable selection methods: what, how and which. Bayesian Anal. 4(1), 85\u2013117 (2009)","DOI":"10.1214\/09-BA403"},{"issue":"1","key":"10582_CR68","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.cels.2020.10.003","volume":"12","author":"KA Overmyer","year":"2021","unstructured":"Overmyer, K.A., Shishkova, E., Miller, I.J., Balnis, J., Bernstein, M.N., Peters-Clarke, T.M., Meyer, J.G., Quan, Q., Muehlbauer, L.K., Trujillo, E.A., et al.: Large-scale multi-omic analysis of COVID-19 severity. Cell Syst. 12(1), 23\u201340 (2021)","journal-title":"Cell Syst."},{"issue":"482","key":"10582_CR69","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1198\/016214508000000337","volume":"103","author":"T Park","year":"2008","unstructured":"Park, T., Casella, G.: The bayesian lasso. J. Am. Stat. Assoc. 103(482), 681\u2013686 (2008)","journal-title":"J. Am. Stat. Assoc."},{"key":"10582_CR70","unstructured":"Piironen, J., Vehtari, A.: On the hyperprior choice for the global shrinkage parameter in the horseshoe prior. Artif. Intell. Stat.\u00a0PMLR (2017)"},{"issue":"521","key":"10582_CR71","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1080\/01621459.2016.1260469","volume":"113","author":"V Ro\u010dkov\u00e1","year":"2018","unstructured":"Ro\u010dkov\u00e1, V., George, E.I.: The spike-and-slab lasso. J. Am. Stat. Assoc. 113(521), 431\u2013444 (2018)","journal-title":"J. Am. Stat. Assoc."},{"issue":"11\u201312","key":"10582_CR72","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1002\/sim.4439","volume":"31","author":"V Ro\u010dkov\u00e1","year":"2012","unstructured":"Ro\u010dkov\u00e1, V., Lesaffre, E., Luime, J., L\u00f6wenberg, B.: Hierarchical Bayesian formulations for selecting variables in regression models. Stat. Med. 31(11\u201312), 1221\u20131237 (2012)","journal-title":"Stat. Med."},{"key":"10582_CR73","doi-asserted-by":"crossref","unstructured":"Schwarz G.: Estimating the dimension of a model. The Ann. Stat. 461\u2013464 (1978)","DOI":"10.1214\/aos\/1176344136"},{"issue":"4","key":"10582_CR74","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1214\/088342304000000297","volume":"19","author":"SJ Sheather","year":"2004","unstructured":"Sheather, S.J.: Density Estimation. Stat. Sci. 19(4), 588\u2013597 (2004)","journal-title":"Stat. Sci."},{"key":"10582_CR75","doi-asserted-by":"crossref","unstructured":"Sheather, S.J., Jones, M.C.: A reliable data-based bandwidth selection method for kernel density estimation. J. Roy. Stat. Soc.: Ser. B (Methodol.) 53(3), 683\u2013690 (1991)","DOI":"10.1111\/j.2517-6161.1991.tb01857.x"},{"issue":"1","key":"10582_CR76","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.cell.2020.05.032","volume":"182","author":"B Shen","year":"2020","unstructured":"Shen, B., Yi, X., Sun, Y., Bi, X., Du, J., Zhang, C., Quan, S., Zhang, F., Sun, R., Qian, L., et al.: Proteomic and metabolomic characterization of covid-19 patient sera. Cell 182(1), 59\u201372 (2020)","journal-title":"Cell"},{"key":"10582_CR77","doi-asserted-by":"crossref","DOI":"10.1201\/9781003089018","volume-title":"Handbook of bayesian variable selection","author":"MG Tadesse","year":"2021","unstructured":"Tadesse, M.G., Vannucci, M.: Handbook of bayesian variable selection. CRC Press (2021)"},{"issue":"5","key":"10582_CR78","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S2215-0366(21)00084-5","volume":"8","author":"M Taquet","year":"2021","unstructured":"Taquet, M., Geddes, J.R., Husain, M., Luciano, S., Harrison, P.J.: 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. The Lancet Psychiatry 8(5), 416\u2013427 (2021)","journal-title":"The Lancet Psychiatry"},{"key":"10582_CR79","doi-asserted-by":"crossref","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc. Ser. B Stat Methodol. 58(1), 267\u2013288 (1996)","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"issue":"4","key":"10582_CR80","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1214\/17-BA1065","volume":"12","author":"S van der Pas","year":"2017","unstructured":"van der Pas, S., Szab\u00f3, B., van der Vaart, A.: Uncertainty quantification for the horseshoe (with discussion). Bayesian Anal. 12(4), 1221\u20131274 (2017)","journal-title":"Bayesian Anal."},{"key":"10582_CR81","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.jmp.2018.12.004","volume":"89","author":"S Van Erp","year":"2019","unstructured":"Van Erp, S., Oberski, D.L., Mulder, J.: Shrinkage priors for bayesian penalized regression. J. Math. Psychol. 89, 31\u201350 (2019)","journal-title":"J. Math. Psychol."},{"issue":"8","key":"10582_CR82","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0272867","volume":"17","author":"L Vig\u00f3n","year":"2022","unstructured":"Vig\u00f3n, L., Gal\u00e1n, M., Torres, M., Mart\u00edn-Galiano, A.J., Rodr\u00edguez-Mora, S., Mateos, E., Corona, M., Malo, R., Navarro, C., Murciano-Ant\u00f3n, M.A., et al.: Association between hla-c alleles and covid-19 severity in a pilot study with a spanish mediterranean caucasian cohort. PLoS ONE 17(8), e0272867 (2022)","journal-title":"PLoS ONE"},{"issue":"3","key":"10582_CR83","first-page":"753","volume":"12","author":"R Vivekananda","year":"2017","unstructured":"Vivekananda, R., Chakraborty, S.: Selection of tuning parameters, solution paths and standard errors for Bayesian lassos. Bayesian Anal. 12(3), 753\u2013778 (2017)","journal-title":"Bayesian Anal."},{"key":"10582_CR84","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1007\/s11222-019-09914-9","volume":"30","author":"F Wang","year":"2020","unstructured":"Wang, F., Mukherjee, S., Richardson, S., Hill, S.M.: High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking. Stat. Comput. 30, 697\u2013719 (2020)","journal-title":"Stat. Comput."},{"issue":"1","key":"10582_CR85","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/s41421-021-00296-9","volume":"7","author":"X Wang","year":"2021","unstructured":"Wang, X., Wen, Y., Xie, X., Liu, Y., Tan, X., Cai, Q., Zhang, Y., Cheng, L., Xu, G., Zhang, S., et al.: Dysregulated hematopoiesis in bone marrow marks severe COVID-19. Cell Discov. 7(1), 60 (2021)","journal-title":"Cell Discov."},{"issue":"12","key":"10582_CR86","doi-asserted-by":"crossref","first-page":"2054","DOI":"10.1038\/s41591-021-01618-w","volume":"27","author":"P Webster","year":"2021","unstructured":"Webster, P.: COVID-19 timeline of events. Nat. Med. 27(12), 2054\u20132055 (2021)","journal-title":"Nat. Med."},{"key":"10582_CR87","volume":"13","author":"S Wu","year":"2022","unstructured":"Wu, S., Xu, Y., Zhang, J., Ran, X., Jia, X., Wang, J., Sun, L., Yang, H., Li, Y., Fu, B., et al.: Longitudinal serum proteome characterization of COVID-19 patients with different severities revealed potential therapeutic strategies. Front. Immunol. 13, 893943 (2022)","journal-title":"Front. Immunol."},{"key":"10582_CR88","first-page":"909","volume":"4","author":"X Xu","year":"2015","unstructured":"Xu, X., Ghosh, M.: Bayesian variable selection and estimation for group lasso. Bayesian Anal. 4, 909\u2013936 (2015)","journal-title":"Bayesian Anal."},{"key":"10582_CR89","unstructured":"Zellner, A.: On assessing prior distributions and Bayesian regression analysis with g-prior distributions. Bayesian inference and decision techniques (1986)"},{"issue":"538","key":"10582_CR90","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1080\/01621459.2020.1825449","volume":"117","author":"YD Zhang","year":"2022","unstructured":"Zhang, Y.D., Naughton, B.P., Bondell, H.D., Reich, B.J.: Bayesian regression using a prior on the model fit: The r2\u2013d2 shrinkage prior. J. Am. Stat. Assoc. 117(538), 862\u2013874 (2022)","journal-title":"J. Am. Stat. Assoc."},{"issue":"2","key":"10582_CR91","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou, H., Hastie, T.: Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B Stat Methodol. 67(2), 301\u2013320 (2005)","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."}],"container-title":["Statistics and Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-025-10582-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11222-025-10582-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-025-10582-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T16:15:49Z","timestamp":1740586549000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11222-025-10582-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,20]]},"references-count":91,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["10582"],"URL":"https:\/\/doi.org\/10.1007\/s11222-025-10582-1","relation":{},"ISSN":["0960-3174","1573-1375"],"issn-type":[{"type":"print","value":"0960-3174"},{"type":"electronic","value":"1573-1375"}],"subject":[],"published":{"date-parts":[[2025,2,20]]},"assertion":[{"value":"25 December 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 February 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"53"}}