TY - JOUR
T1 - Cross-validation for comparing multiple density estimation procedures
AU - Lian, Heng
PY - 2009/1/1
Y1 - 2009/1/1
N2 - We demonstrate the consistency of cross-validation for comparing multiple density estimators using simple inequalities on the likelihood ratio. In nonparametric problems, the splitting of data does not require the domination of test data over the training/estimation data, contrary to Shao [Shao, J., 1993. Linear model selection by cross-validation. J. Amer. Statist. Assoc. 88, 486-494]. The result is complementary to that of Yang [Yang, Y., 2007. Consistency of cross-validation for comparing regression procedures, Ann. Statist. 35, 2450-2473; Yang, Y., 2006. Comparing learning methods for classification. Statist. Sinica 16, 635-657]. © 2008 Elsevier B.V. All rights reserved.
AB - We demonstrate the consistency of cross-validation for comparing multiple density estimators using simple inequalities on the likelihood ratio. In nonparametric problems, the splitting of data does not require the domination of test data over the training/estimation data, contrary to Shao [Shao, J., 1993. Linear model selection by cross-validation. J. Amer. Statist. Assoc. 88, 486-494]. The result is complementary to that of Yang [Yang, Y., 2007. Consistency of cross-validation for comparing regression procedures, Ann. Statist. 35, 2450-2473; Yang, Y., 2006. Comparing learning methods for classification. Statist. Sinica 16, 635-657]. © 2008 Elsevier B.V. All rights reserved.
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U2 - 10.1016/j.spl.2008.07.029
DO - 10.1016/j.spl.2008.07.029
M3 - RGC 21 - Publication in refereed journal
SN - 0167-7152
VL - 79
SP - 112
EP - 115
JO - Statistics and Probability Letters
JF - Statistics and Probability Letters
IS - 1
ER -