{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:58:18Z","timestamp":1780603098205,"version":"3.54.1"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,4,21]],"date-time":"2015-04-21T00:00:00Z","timestamp":1429574400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Comput Stat"],"published-print":{"date-parts":[[2016,3]]},"DOI":"10.1007\/s00180-015-0577-7","type":"journal-article","created":{"date-parts":[[2015,4,20]],"date-time":"2015-04-20T05:22:45Z","timestamp":1429507365000},"page":"269-289","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Practical use of robust GCV and modified GCV for spline smoothing"],"prefix":"10.1007","volume":"31","author":[{"given":"Mark A.","family":"Lukas","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank R.","family":"de Hoog","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert S.","family":"Anderssen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2015,4,21]]},"reference":[{"key":"577_CR1","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1007\/BF02170998","volume":"12","author":"PM Anselone","year":"1968","unstructured":"Anselone PM, Laurent PJ (1968) A general method for the construction of interpolating or smoothing spline-functions. Numer Math 12:66\u201382","journal-title":"Numer Math"},{"key":"577_CR2","unstructured":"Cox DD (1984) Gaussian approximation of smoothing splines. Tech. rep., Dept. Statist., University of Wisconsin\/Madison"},{"key":"577_CR3","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1007\/BF01404567","volume":"31","author":"P Craven","year":"1979","unstructured":"Craven P, Wahba G (1979) Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalized cross-validation. Numer Math 31:377\u2013403","journal-title":"Numer Math"},{"key":"577_CR4","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1198\/016214501750332811","volume":"96","author":"DJ Cummins","year":"2001","unstructured":"Cummins DJ, Filloon TG, Nychka D (2001) Confidence intervals for nonparametric curve estimates: toward more uniform pointwise coverage. J Am Stat Assoc 96:233\u2013246","journal-title":"J Am Stat Assoc"},{"issue":"275","key":"577_CR5","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1090\/S0025-5718-2011-02451-8","volume":"80","author":"FR Hoog de","year":"2011","unstructured":"de Hoog FR, Anderssen RS, Lukas MA (2011) Differentiation of matrix functionals using triangular factorization. Math Comput 80(275):1585\u20131600","journal-title":"Math Comput"},{"key":"577_CR6","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1214\/aos\/1009210549","volume":"29","author":"B Efron","year":"2001","unstructured":"Efron B (2001) Selection criteria for scatterplot smoothers. Ann Stat 29:470\u2013504","journal-title":"Ann Stat"},{"key":"577_CR7","volume-title":"Spline smoothing and nonparametric regression","author":"RL Eubank","year":"1988","unstructured":"Eubank RL (1988) Spline smoothing and nonparametric regression. Dekker, New York"},{"key":"577_CR8","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1080\/10485250903095820","volume":"22","author":"DA Girard","year":"2010","unstructured":"Girard DA (2010) Estimating the accuracy of (local) cross-validation via randomised GCV choices in kernel or smoothing spline regression. J Nonparametric Stat 22:41\u201364","journal-title":"J Nonparametric Stat"},{"key":"577_CR9","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-4473-3","volume-title":"Nonparametric regression and generalized linear models: a roughness penalty approach","author":"PJ Green","year":"1994","unstructured":"Green PJ, Silverman BW (1994) Nonparametric regression and generalized linear models: a roughness penalty approach. Chapman & Hall, London"},{"key":"577_CR10","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-3683-0","volume-title":"Smoothing spline ANOVA models","author":"C Gu","year":"2002","unstructured":"Gu C (2002) Smoothing spline ANOVA models. Springer, New York"},{"key":"577_CR11","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1007\/BF01389878","volume":"47","author":"MF Hutchinson","year":"1985","unstructured":"Hutchinson MF, de Hoog FR (1985) Smoothing noisy data with spline functions. Numer Math 47:99\u2013106","journal-title":"Numer Math"},{"key":"577_CR12","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1046\/j.1369-7412.2003.05316.x","volume":"66","author":"YJ Kim","year":"2004","unstructured":"Kim YJ, Gu C (2004) Smoothing spline Gaussian regression: more scalable computation via efficient approximation. J R Stat Soc Ser B 66:337\u2013356","journal-title":"J R Stat Soc Ser B"},{"key":"577_CR13","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1214\/aos\/1176350052","volume":"14","author":"KC Li","year":"1986","unstructured":"Li KC (1986) Asymptotic optimality of $$C_L$$ C L and generalized cross-validation in ridge regression with application to spline smoothing. Ann Stat 14:1101\u20131112","journal-title":"Ann Stat"},{"key":"577_CR14","doi-asserted-by":"crossref","first-page":"1883","DOI":"10.1088\/0266-5611\/22\/5\/021","volume":"22","author":"MA Lukas","year":"2006","unstructured":"Lukas MA (2006) Robust generalized cross-validation for choosing the regularization parameter. Inverse Probl 22:1883\u20131902","journal-title":"Inverse Probl"},{"issue":"034","key":"577_CR15","first-page":"006","volume":"24","author":"MA Lukas","year":"2008","unstructured":"Lukas MA (2008) Strong robust generalized cross-validation for choosing the regularization parameter. Inverse Probl 24(034):006","journal-title":"Inverse Probl"},{"key":"577_CR16","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.jspi.2014.05.006","volume":"153","author":"MA Lukas","year":"2014","unstructured":"Lukas MA (2014) Performance criteria and discrimination of extreme undersmoothing in nonparametric regression. J Stat Plan Inference 153:56\u201374","journal-title":"J Stat Plan Inference"},{"key":"577_CR17","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.cam.2010.05.016","volume":"235","author":"MA Lukas","year":"2010","unstructured":"Lukas MA, de Hoog FR, Anderssen RS (2010) Efficient algorithms for robust generalized cross-validation spline smoothing. J Comput Appl Math 235:102\u2013107","journal-title":"J Comput Appl Math"},{"key":"577_CR18","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1111\/j.1467-9469.2011.00736.x","volume":"39","author":"MA Lukas","year":"2012","unstructured":"Lukas MA, de Hoog FR, Anderssen RS (2012) Performance of robust GCV and modified GCV for spline smoothing. Scand J Stat 39:97\u2013115","journal-title":"Scand J Stat"},{"key":"577_CR19","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1214\/aos\/1176347508","volume":"18","author":"D Nychka","year":"1990","unstructured":"Nychka D (1990) The average posterior variance of a smoothing spline and a consistent estimate of the average squared error. Ann Stat 18:415\u2013428","journal-title":"Ann Stat"},{"key":"577_CR20","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/BF02162161","volume":"10","author":"CH Reinsch","year":"1967","unstructured":"Reinsch CH (1967) Smoothing by spline functions. Numer Math 10:177\u2013183","journal-title":"Numer Math"},{"key":"577_CR21","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1007\/BF02169154","volume":"16","author":"CH Reinsch","year":"1971","unstructured":"Reinsch CH (1971) Smoothing by spline functions II. Numer Math 16:451\u2013454","journal-title":"Numer Math"},{"key":"577_CR22","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1080\/03610928908829916","volume":"18","author":"T Robinson","year":"1989","unstructured":"Robinson T, Moyeed R (1989) Making robust the cross-validatory choice of smoothing parameter in spline smoothing regression. Commun Stat Theory Methods 18:523\u2013539","journal-title":"Commun Stat Theory Methods"},{"key":"577_CR23","doi-asserted-by":"crossref","DOI":"10.1137\/1.9781611970128","volume-title":"Spline models for observational data","author":"G Wahba","year":"1990","unstructured":"Wahba G (1990) Spline models for observational data. SIAM, Philadelphia"}],"container-title":["Computational Statistics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-015-0577-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00180-015-0577-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-015-0577-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,23]],"date-time":"2019-05-23T18:36:56Z","timestamp":1558636616000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00180-015-0577-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,4,21]]},"references-count":23,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,3]]}},"alternative-id":["577"],"URL":"https:\/\/doi.org\/10.1007\/s00180-015-0577-7","relation":{},"ISSN":["0943-4062","1613-9658"],"issn-type":[{"value":"0943-4062","type":"print"},{"value":"1613-9658","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,4,21]]}}}