Stratification Method Using κ-Spatial Medians Clustering

Title & Authors
Stratification Method Using κ-Spatial Medians Clustering
Son, Soon-Chul; Jhun, Myoung-Shic;

Abstract
Stratification of population is widely used to improve the efficiency of the estimation in a sample survey. However, it causes several problems when there are some variables containing outliers. To overcome these problems, Park and Yun (2008) proposed a rather subjective method, which finds outliers before $\small{\kappa}$-means clustering for stratification. In this study, we propose the $\small{\kappa}$-spatial medians clustering method which is more robust than $\small{\kappa}$-means clustering method and also does not need the process of finding outliers in advance. We investigate the characteristics of the proposed method through a case study used in Park and Yun (2008) and confirm the efficiency of the proposed method.㴍舀܀㘲㌮〵㬬B畩汤楮本⁣潮獴牵捴楯渠慮搠捩癩氠敮杩湥敲楮最
Keywords
$\small{\kappa}$-means clustering;$\small{\kappa}$-spatial medians clustering;multivariate stratification;Neyman allocation;outliers;
Language
Korean
Cited by
References
1.
농촌진흥청 (2006). <2006 농촌생활지표>, 농촌진흥청

2.
박진우, 윤석훈 (2008). 이상점을 고려한 다변량 층화, <응용통계연구>, 21, 377-385

3.
통계청 (2006). <2005 인구주택총조사>, 통계청

4.
Brown, B. M. (1983). Statistical uses of the spatial median, Journal of the Royal Statistical Society. Series B, 45, 25-30

5.
Cuests-Albertos, J. A., Gordaliza, A. and Matran, C. (1997). Grand tour and projection pursuit, Journal of Computational and Graphical Statistics, 4, 155-172

6.
Golder, P. A. and Yeomans, K. A. (1973). The use of cluster analysis for stratification, Applied Statistics, 22, 213-219

7.
Jarque, C. M. (1981). A solution to the problem of optimum stratification in multivariate sampling, Journal of the Royal Statistical Society. Series C (Applied Statistics), 30, 163-169

8.
Jin, S. (1999). A study on the partitioning method for cluster analysis, 박사학위논문, 고려대학교

9.
Lavallee, P. and Hidiroglou, M. A. (1998). On the stratification of skewed populations, Survey Methodology, 14, 33-43

10.
Milligan, G. W. (1980). An examination of the effect of six types of error perturbation of fifteen clustering algorithms, Psychometrika, 45, 325-342

11.
Milligan, G. W. (1981). A review of Monte Carlo tests of cluster analysis, Multivariate Behavioral Research, 16, 379-407

12.
Schuenemeyer, J. H. (1975). Maximum eccentricity as a union-intersection test in multivariate analysis, Geogia University, Athens