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http://dx.doi.org/10.5351/KJAS.2011.24.6.1249

On the Use of Sequential Adaptive Nearest Neighbors for Missing Value Imputation  

Park, So-Hyun (Department of Statistics, Korea University)
Bang, Sung-Wan (Department of Mathematics, Korea Military Academy)
Jhun, Myoung-Shic (Department of Statistics, Korea University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.6, 2011 , pp. 1249-1257 More about this Journal
Abstract
In this paper, we propose a Sequential Adaptive Nearest Neighbor(SANN) imputation method that combines the Adaptive Nearest Neighbor(ANN) method and the Sequential k-Nearest Neighbor(SKNN) method. When choosing the nearest neighbors of missing observations, the proposed SANN method takes the local feature of the missing observations into account as well as reutilizes the imputed observations in a sequential manner. By using a Monte Carlo study and a real data example, we demonstrate the characteristics of the SANN method and its potential performance.
Keywords
Adaptive nearest neighbors; imputation; k-nearest neighbors; missing data;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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