• Asian Pacific Journal of Cancer Prevention
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• 제13권7호
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• pp.3229-3232
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• 2012

In this study, cancer incidence data were assessed to provide various rates of five year age groups for a given year, lying between two census years. The individual exponential growth rate method is most useful in both population-based and non-population cased cancer registries in India to estimate the population by five yearly age groups and also find the rates of crude rates, age standard rates and cumulative rates. This method has been shown to endure from bias and often results sacrificing the overall growth rate and correction factor must be needful in five year age group population to maintain it. A second method, the difference distribution method is also able to maintain the overall growth rate and overcome the bias in estimation of five yearly age group populations. From this point of view these methods serving a new technique for population estimation by five yearly age groups for inter census years.

• 대한지리학회지
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• 제45권6호
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• pp.806-819
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• 2010

센서스 단위의 인구자료는 기초적인 인문사회 자료로 행정구역 단위로 요약되어 공간분석에 시용된다. 정밀한 인구 분포를 추정하기 위해 기존의 연구에서는 위성영상과 회귀분석 모형을 이용하였다. 하지만 회귀식에 의한 추정치는 공간자료의 공간적자기상관과 잔차 때문에 정확도에 있어 한계가 있었다. 본 연구는 회귀모형과 회귀모형에서 추출된 잔차에 대해 공간적자기상관을 고려하도록 크리깅 보간하는 RK모형(Regression Kriging Model)을 이용하여 인구분포의 추정 정확도를 향상하였다. RK모형을 적용하여 서울시의 4개구를 대상으로 사례분석을 하였으며, 모형의 효율성을 검증하기 위해 회귀분석만을 이용한 예측 결과와 RK모형을 이용한 예측 결과를 서로 비교하였다. 비교한 결과로 상관관계 계수 평균제곱근 오차, G 통계량 수치에서 RK모형의 추정 정확도가 기존의 회귀모형에 비해 높게 나온 것을 확인할수 있었다. 향후 정확한 인구추정을 위해 RK모형이 많이 활용될 수 있을 것이다.

• 한국지리정보학회지
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• 제19권3호
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• pp.127-143
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• 2016

본 연구는 상이한 셀 크기에 따라 밀도구분적 인구추정의 정확성이 어떻게 변화하는지를 탐색하였다. 미국 조지아주 풀턴 카운티를 사례로 한 밀도구분적 인구 지도가 지능적인 밀도구분적 지도제작기법, 인구자료, 원본 및 모의된 토지이용 및 피복 자료를 이용하여 30m에서 420m의 해상도까지 매 30m 간격으로 생성되었다. 밀도구분적 인구 지도의 정확성은 RMSE 및 수정 RMSE 통계치를 이용하여 평가되었다. 프랙털 차원 값은 TPSA 방법을 사용하면서 30m에서 420m의 해상도까지 생성된 밀도구분적 인구 지도에 대해 각각 계산되었다. 연구결과에 따르면, 속성의 정확성 측면에서 인구를 보다 정확하게 추정하기 위해서 210m 이하의 격자 셀 크기가 적절하였나, 사례지역에서 밀도구분적 인구추정의 허용가능한 공간적 정확성을 충족시키기 위해 30m의 격자 셀 크기가 적절하였다. 또한, 프랙털 분석은 120m의 격자 셀 크기가 사례지역에서 밀도구분적 인구추정을 위한 최적의 해상도 이다는 것을 보여준다.

• 환경영향평가
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• 제22권5호
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• pp.525-528
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• 2013

River otter(Lutra lutra) are listed as endangered species and Natural monument in Korea, and this study examined the possibility of extinct of river otter in Hongchon river using with the application of Population Viability Analysis (PVA) technique. In Hongchon river areas population was estimated 9 individuals for the last 1999-2005 years and PVA analysis was done for the next 10 years using the average population of 9. Using the initial population the river otter was estimated 30% of extinct for the next 10 years. This estimation was quite low considering water pollution and construction of highways. Also PVA only used population size lacking in other life history information. Nonetheless river otter population can be in risk of extinction if the current construction of crossovers, cement bank are maintained. Long term information regarding life history needs essential.

• 환경영향평가
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• 제18권5호
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• pp.293-299
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• 2009

Wintering migratory species of white-fronted geese (Anser albifrons) are common visitor in South Korea, and this study examined the survivorship of white-fronted geese in the Junam Reservoir with the application of Population Viability Analysis (PVA) technique. In Junam PVA analysis was done for the next 50 years using factors of breeding population, sex ratios, survivorship in the VORTEX program. As a result white-fronted geese will reach to carrying capacity within 40 years, and population will reach to carrying capacity later when it becomes smaller. Also with a large initial population white-fronted geese will reach to carrying capacity earlier. In conclusion, for the next 50 years the white-fronted geese are expected to a long-term survival with stable condition with survivorship (0.03) and extinction rate (0.0).

• 한국측량학회지
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• 제33권3호
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• pp.145-153
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• 2015

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density

• 응용통계연구
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• 제31권5호
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• pp.621-636
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• 2018

정보적 표본설계 기법을 적용하여 무응답의 영향을 줄이기 위한 연구가 진행되고 있다. 특히 초모집단모형(super population model)에 포함된 오차의 분포가 정규분포를 따르고 응답률이 지수함수를 따를 때 지수형 응답률 정보를 모수추정에 사용함으로써 추정의 정확성이 향상되는 것으로 알려져 있다. 최근 Chung과 Shin (2017)은 정보적 표본설계의 가중치를 구하기 위해 세부 층을 등간격으로 나누는 방법을 고려하였으며 세부 층의 개수가 추정의 정확성에 영향을 주는 것을 확인하였다. 이에 본 연구에서는 주어진 표본 규모에 따른 최적의 세부 층 개수와 최적의 층 경계를 구하기 위해 등간격, 분위수, LH 알고리즘을 이용하여 층을 나누는 방법을 살펴보았으며 모의실험을 통하여 각 방법의 결과를 비교하였다. 또한 다양한 형태의 보조변수 분포를 이용하여 실무에서 사용할 수 있는 세부 층 경계와 세부 층 개수를 정하는 기준을 제안하였다.

• Journal of Preventive Medicine and Public Health
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• 제42권2호
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• pp.130-134
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• 2009

Objectives : A method of estimation using 8 populationbased cancer registries databases in Korea(KRCR DB) has been introduced as another strategy for validly estimating the national cancer incidence(NCI) in Korea. The purpose of this study was to evaluate the validity of this method with using the 7 KRCR DBs, excluding Seoul covering 21% of the total population of Korea. Methods : We designed the study method(NCSE_7) as same as the estimating method with using 8 KRCR DBs (NCSE_8) in order to ensure maximal comparability. We defined the expected number of cancer cases in each registry as the number of observed cases and then we added the weighted observed cases according to gender, age and the proportion of the population covered by each registry for the population of the seven regions and the population of all areas, with excluding these seven regions. From the expected number of total cancer incidents, the estimated NCI was calculated by dividing the expected number of cancer cases by the number of the total population. The standard error(SE) of the estimated incidence was also taken from the expected number of total cancer incidents. Results : Compared with the results of the NCSE_8, the overall age-standardized rates(ASR) in men and women became over-estimated and under-estimated, respectively. Primary sites that showed statistically significant differences were the colo-rectum, prostate, breast and thyroid. The index of death certificate only(DCO)and microscopically verified(MV)% indicating levels of data quality were decreased, especially for the brain in DCO% and kidney in the MV%. Conclusions : The database of Seoul regional cancer registry has a key role for the method to estimate the valid nationwide cancer statistics in Korea with using the population-based cancer registries databases.

• 응용통계연구
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• 제16권2호
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• pp.239-246
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• 2003

소지역에서 직접(direct) 시계열추정을 할 수 있다면, 소지역들 추정에서 최적선형 불편 예측량(BLUP)을 일반화 시킬 수 있다. 특히 조사에서 얻어지는 관측 값의 오차가 시간상으로 상관관계가 있다면 Kalman Filter(KF)기법이 사용 될 수 있다. 이 연구는 예측 값을 활용한 소지역의 실업자 수 추정에서 표본으로 추출되지 않은, 즉 관측되지 않은 값의 예측모형에 KF기법을 적용하였다. 이는 경제활동인구수를 이용하여 현 시점의 소지역 실업자 수를 예측함수(BLUP)를 통해 추정하게 된다. 그리고 이를 단순 회귀분석 추정치와 비교하였다.

• Journal of Preventive Medicine and Public Health
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• 제41권6호
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• pp.380-386
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• 2008

Objectives: Valid data on the national cancer incidence (NCI) is the data should be needed to plan, monitor and evaluate the national cancer control programs. The purpose of this study was to estimate the NCI for 2000-2002 from 8 population-based cancer registries database in Korea (KRCR DB). Methods: We defined the expected number of cancer cases in each registry as the number of observed cases and then adding to the weighted observed cases, according to sex, age groups, and the proportion of the population covered by each registry for the population of the eight regions and the population of all areas with excluding the 8 regions. From the expected number of total cancer incidents, he estimated NCI was calculated by dividing the expected number of cancer cases by he umber of the total population. The standard error (SE) of the estimated incidence was also taken from the expected number of total cancer incidents. Results: The overall estimated crude rates in 2000-2002 ere 267.1 and 219.0 per 100,000 for men and women, respectively. The overall age-standardized rates (ASR) were 290.1 and 180.7 per 100,000, respectively. Compared with the ASRs obtained from Korea National Cancer Incidence database (KNCI DB), the estimated ASRs from the KRCR DB did not show statistically significant differences except for some cancers in women. For the aspect of the SE, index of DCO(death certificate only) and of MV(microscopically verified), the estimated ASRs from the KRCR DB are more accurate and they have higher quality rather than the calculated ASRs from the KNCI DB. Conclusions: We found that this developed method using the KRCR DB is valid and it could be another strategy for estimating the NCI in Korea.