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On the Use of Sequential Adaptive Nearest Neighbors for Missing Value Imputation
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 Title & Authors
On the Use of Sequential Adaptive Nearest Neighbors for Missing Value Imputation
Park, So-Hyun; Bang, Sung-Wan; Jhun, Myoung-Shic;
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 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;
 Language
Korean
 Cited by
1.
K 최대근접이웃 방법을 이용한 통행시간 예측에 대한 연구,임성한;이향미;박성룡;허태영;

응용통계연구, 2013. vol.26. 5, pp.835-845 crossref(new window)
1.
A Study of Travel Time Prediction using K-Nearest Neighborhood Method, Korean Journal of Applied Statistics, 2013, 26, 5, 835  crossref(new windwow)
2.
On the Use of Weighted k-Nearest Neighbors for Missing Value Imputation, Korean Journal of Applied Statistics, 2015, 28, 1, 23  crossref(new windwow)
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