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On the use of adaptive nearest neighbors for missing value imputation

Authors
Jhun, MyoungshicJeong, Hyeong ChulKoo, Ja-Yong
Issue Date
2007
Publisher
TAYLOR & FRANCIS INC
Keywords
adaptive choice; imputation; k-nearest neighbors; local features
Citation
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v.36, no.6, pp.1275 - 1286
Indexed
SCIE
SCOPUS
Journal Title
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume
36
Number
6
Start Page
1275
End Page
1286
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/123096
DOI
10.1080/03610910701569069
ISSN
0361-0918
Abstract
A popular nonparametric treatment of missing value imputation uses methods based on k-nearest neighbors, where the number k of nearest neighbors is fixed without any consideration of the local features of missing values. This article proposes an alternative imputation method based on adaptive nearest neighbors, which takes into account the local features of the data. The proposed method adapts the number of neighbors in imputing the missing values according to the location of the missing values. Efficiency evaluation is then gauged through simulation studies using both simulated and real data. It is shown that the proposed method has distinct advantages over the imputation method based on k-nearest neighbors.
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