Large sample properties of cross-validation assessment statistics
type: Item
instance of: scholarly article
title: Large sample properties of cross-validation assessment statistics
zbMATH Open document ID: 0629.62026
DOI: 10.1016/0378-3758(86)90084-4
author: Harald K. Iverson
author: Ronald Herman Randles
published in: Journal of Statistical Planning and Inference
publication date: 1986-01-01T00:00:00Z
review text: Asymptotic properties are developed for two classes of cross-validation assessment statistics. The two correspond to a large number of small partition sets and a small number of large partition sets. Conditions implying weak convergence, strong convergence, and asymptotic normality are presented for each class. A discriminant analysis misclassification estimator and a regression analysis estimator of absolute error are used to illustrate the general theory.
Mathematics Subject Classification ID: 62E20
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 4024509
zbMATH Keywords: U-statistics
zbMATH Keywords: consistency
zbMATH Keywords: cross-validation assessment statistics
zbMATH Keywords: large number of small partition sets
zbMATH Keywords: small number of large partition sets
zbMATH Keywords: weak convergence
zbMATH Keywords: strong convergence
zbMATH Keywords: asymptotic normality
zbMATH Keywords: discriminant analysis misclassification estimator
zbMATH Keywords: regression analysis estimator of absolute error
MaRDI profile type: Publication
full work available at URL: 0378-3758(86)90084-4
OpenAlex ID: W2000646974
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description: scientific article; zbMATH DE number 4024509