• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.131-136
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• 2003

소지역에서 유한모집단의 총계등을 추정하는데 있어서 모형-기반 합성치를 예측한다. 즉, 예측(prediction) 문제로 추정치를 다룬다. 초모집단(super-population) 확률 모형을 세우고 최적의 예측치를 유도한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.479-485
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• 2011

A number of case studies that find distribution of longevity population and influencing factors through the spatial data fusion using GIS techniques are growing. The majority cases of these studies are adopt census administrative boundary data for the spatial analysis. However, these methods cannot fully explain the phenomenon of longevity because there are a variety of spatial characteristics within the census administrative boundaries. Therefore, studies of spatial unit are required that realistically reflect the phenomenon of human longevity. The dasymetric mapping method enables to product of spatial unit more realistic than census administrative boundary map and statistic estimates of small area utilizing diversity spatial information. In this study, elderly population of small area has been estimated within statistically significant level that applied the vector based dasymetric mapping method. Also, the cluster analysis confirmed that the variation of local spatial relationship within census administrative boundary. The result of this study implied that the need for local-level studies of the human longevity and the validity of the dashmetric mapping techniques.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.387-397
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• 2008

Recently many researches on data analysis using spatial statistics have been studied in various field and the studies on small area estimations using spatial statistics are in actively progress. In analysis of lattice data, defining the neighborhood information system is the most crucial procedure because it also determines the result of the analysis. However the used neighborhood informal ion system is generally defined by sharing the common border lines of small areas. In this paper the other neighborhood information systems are introduced and those systems are compared with Moran's I statistic and for the comparisons, Economic Active Population Survey (2001) is used.

• Survey Research
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• v.1 no.1
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• pp.1-19
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• 2000

The present status of utilizing statistics and problems in the era of information and localization are summarized and the developing process in a computerized survey is investigated. Also, characteristics and development plans of the internet surveys to come, which can substitute for telephone surveys, are discussed. We introduced small area estimation for producing the local statistics and suggested the standardization of statistics of improve statistics use and avoid misunderstanding in various areas of studies.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.337-347
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• 2010

Most sample surveys are designed to estimate reliable statistics for the whole population and for some large subpopulations. However, the research for small area estimation have been increasing in recent years because users demand to reliable estimates for smaller subpopulations like small areas or specific domains. In Korea, the Economically Active Population Survey(EAPS) is the main household survey that produces monthly unemployment rates for nationwide and 16 large areas (7 metropolitans and 9 provinces) in Korea. For county level estimation, direct estimators are not reliable because of the small sample sizes. We consider small area estimation of the county level unemployment ratesfrom the sample observations in EAPS. To do this, we use an area level model to "borrow strength" from the auxiliary information, such as administrative data and census data. The proposed method is based on the assumption of normality of the model errors in the area level model. The proposed method is compared with the other alternatives in terms of the estimated mean squared errors.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.431-443
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• 2004

For the purpose of disease mapping, we consider the four small area estimation techniques to estimate the mortality rate of small areas; direct, Empirical estimation with total moment estimator and local moment estimator, Estimation based on hierarchial generalized linear model. The estimators are compared by empirical study based on lung cancer mortality data from 2000 Annual Reports on the Cause of Death Statistics in Gyeongsang-Do and Jeonla-Do published by Korean National Statistical Office. Also he stability and efficiency of these estimators are investigated in terms of mean square deviation as well as variation of estimates.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.835-847
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• 2016

To analyze lattice or areal data, a conditionally autoregressive (CAR) model has been widely used in the eld of spatial analysis. The spatial neighborhoods within CAR model are generally formed using only inter-distance or boundaries between regions. Kyung and Ghosh (2010) proposed a new class of models to accommodate spatial variations that may depend on directions. The proposed model, a directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Properties of maximum likelihood estimators of a Gaussian DCAR are discussed. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.141-151
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• 2009

According to the type of microdata, the various methods have been in use for masking microdata. Multiplicative noise is the one of popular schemes for masking continuous variables. In this paper, we introduce the method of masking based on multiplicative noise and show some results of the application on the 2006 Householder Income and Expenditure Survey (HIES) data. To create the multiplicative noise factor, we used the triangular distribution. truncated triangular distribution, trapezoidal distribution, and double triangular distribution. Also, formulas for the domain estimation for the data masked by the multiplicative noise are developed.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1133-1146
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• 2016

Counts or averages over arbitrary regions are often analyzed using conditionally autoregressive (CAR) models. The spatial neighborhoods within CAR model are generally formed using only the inter-distance or boundaries between the sub-regions. Kyung and Ghosh (2009) proposed a new class of models to accommodate spatial variations that may depend on directions, using different weights given to neighbors in different directions. The proposed model, directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Bayesian inference method is discussed based on efficient Markov chain Monte Carlo (MCMC) sampling of the posterior distributions of the parameters. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• Survey Research
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• v.5 no.1
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• pp.103-130
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• 2004

Main monthly household surveys conducted by Korea National Statistical Office are economically active population survey(EAPS) and household income and expenditure survey(HIES). Samples of these two surveys are redesigned every 5 years based on Census. This paper is about sample redesign of household survey conducted in 2002 based on 2000 Census. Main improvements of 2002 sample redesign are the introduction of rotation sampling system, the expansion of HIES survey area from urban to whole country and the foundation of basement to make small area estimation for the unemployment statistics. Also the number of sample households within a enumeration district(ED) is reduced from 24 to 20. That makes it possible to select more ED samples which provides better precision for EAPS and HIES. To select representative samples for the population, different classification index is used for each metropolitan area and provinces.