• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.783-791
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• 2008

Estimation procedure of the finite population proportion and distribution function is considered. Based on a logistic regression model, an approximately model- optimal estimator is defined and conditions for the estimator to be design-consistent are given. Simulation study shows that the model-optimal design-consistent estimator defined under a logistic regression model performs well in estimating the finite population distribution function.

• 대한원격탐사학회지
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• 제36권1호
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.407-416
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• 2001

Sample surveys are usually designed and analyzed to produce estimates for a large area or populations. Therefore, for the small area estimations, sample sizes are often not large enough to give adequate precision. Several small area estimation methods were proposed in recent years concerning with sample sizes. Here, we will compare simple Bayesian approach with Bayesian prediction for small area estimation based on linear regression model. The performance of the proposed method was evaluated through unemployment population data form Economic Active Population(EAP) Survey.

• Journal of Ecology and Environment
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• 제38권4호
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• pp.493-503
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• 2015

This study analyzed how spatial distribution of Himantormia lugubris is affected by the microenvironment in the Antarctic Specially Protected Area (ASPA) No. 171 located in the Barton Peninsula of King George Island that belongs to the maritime Antarctic. In order to determine the population structure of H. lugubris growing in Baekje Hill within ASPA No. 171, we counted the individuals of different size groups after dividing the population into 5 growth stages according to mean diameter as follows: ≤ 1 cm, 1-3 cm, 3-5 cm, 5-10 cm, and ≥ 10 cm. The count of H. lugubris individuals in each growth stage was converted into its percentage with respect to the entire population, which yielded the finding that stages 1 through 5 accounted for 32.8%, 25.3%, 15.9%, 22.5%, and 3.5%, respectively. This suggests that the population of H. lugubris in ASPA No. 171 has a stable reverse J-shaped population structure, with the younger individuals outnumbering mature ones. The mean density of H. lugubris was 17.6/0.25 m², mean canopy cover 13.3%, and the mean dry weight 37.8 g/0.25 m². It began to produce spore in the sizes over 3 cm, and most individuals measuring 5-10 cm were adults with sexually mature apothecia. The spatial distribution of H. lugubris was highly heterogeneous. The major factors influencing its distribution and performance were found to be the period covered by snow, wind direction, moisture, size of the substrate, and canopy cover of Usnea spp. Based on these factors, we constructed a prediction model for estimating the spatial distribution of H. lugubris. Conclusively, the major factors for the spatial distribution of H. lugubris were snow, wind, substrate and the competition with Usnea spp. These results are important for understanding of the distribution in the maritime Antarctic and evolution of H. lugubris that claims a unique life history and ecological niche.

• 한국경제지리학회지
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• 제22권3호
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• pp.351-365
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• 2019

본 연구의 목적은 주요 이동요인별 인구이동 및 인구분포의 시공간적 특징을 분석하고 장래 지역별 인구분포의 변화를 예측하고 전망하는 것이다. 이를 위해 직업, 가족, 주택, 교육 등 주요 이동요인별 거주지 변화로 나타나는 지역별 인구이동의 추이를 파악하고, 장래 지역별 인구 유출입에 의한 인구분포의 변화를 추정하는 예측 시뮬레이션을 진행한다. 분석결과, 거주지를 변경함에 있어 대도시지역과 시 단위 중심의 지리적 이동이 나타나고 있으며 대도시와 시 단위 내에서도 지역별 인구 유출입에 영향을 미치는 주요 이동요인별 구성 비율은 각기 상이하게 나타난다. 또한 이동요인별 시군구별 추이확률과 상태확률을 토대로 6단계-정상 마르코프 연쇄 프로세스를 진행한 결과, 각 이동요인에 따라 장래 시군구별 인구분포의 변화 정도도 차이가 나타날 것으로 추정된다. 본 연구에서 제시하는 방법론과 분석결과는 특히 인구감소로 지방소멸이 우려되는 지역에서 인구의 유입요인은 강화하고 유출요인은 개선하는 지역 맞춤형 인구 및 각종 정책을 계획하고 마련하는데 활용될 수 있다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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• pp.171-176
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• 2003

This paper deals with the problem of predicting order statistics in samples from a Rayleigh population when an outlier is present. Bayesian predictive distribution and prediction bounds of the p-th order statistics is obtained where an outlier of type $\theta\delta$ is present. In this connection, some identies are derived.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• 한국농림기상학회지
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• 제16권4호
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• pp.368-383
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• 2014

기후변화는 곤충의 밀도와 분포, 몸의 형태와 개체의 크기 등 생물학적인 형질 변화, 생식 및 유전적 특성, 그리고 멸종 등에 영향을 미칠 것으로 예상되고 있다. 기후변화의 영향을 예측하여 피해를 줄이기 위해서는 분산되어 있는 곤충 종별 기본적인 생물학적/생태학적 정보들을 종합하여 검토할 필요가 있다. 따라서 본 연구는 기후 및 환경의 변화에 대한 곤충, 특히 해충의 발생 변화 예측에 필요한 생물학적 정보를 정리하여 이를 활용한 미래 피해 예측을 위한 기초 자료를 제공하고자 수행하였다. 또한 국내외 문헌을 비교 분석하여 국내에서 기후변화 연구를 수행하는데 있어 제한 요인들을 확인하고 향후 필요한 연구소요를 제시하고자 하였다. 국내의 연구들은 단기 모니터링 자료를 이용하여 환경 요인과의 관계를 분석하는 수준에 그치고 있는 반면, 국외 연구들은 장기 모니터링 자료를 이용한 분포 변화 분석이나 기 개발된 생물 종의 파라미터를 이용한 발생 및 분포 변화 예측 그리고 곤충 군집의 구성 변화를 모니터링하는 등 다양한 내용을 주제로 기후변화의 영향을 연구하고 있었다. 결론적으로 기후변화에 대응하기 위해서는 체계적인 모니터링 기술 개발을 통해 곤충의 계절발생, 분포, 월동 특성 및 유전적 구조 변화에 대한 연구가 필수적이며, 주요 해충 및 잠재적인 해충에 대한 기후변화의 영향을 예측하기 위해 곤충 개체군 모델의 개발 역시 중요한 부분이 될 것이다.

• 농업과학연구
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• 제42권4호
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• pp.397-406
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• 2015

Quantitative traits are mostly controlled by a large number of genes. Some of these genes tend to have a large effect on quantitative traits in cattle and are known as major genes primarily located at quantitative trait loci (QTL). The genetic merit of animals can be estimated by genomic selection, which uses genome-wide SNP panels and statistical methods that capture the effects of large numbers of SNPs simultaneously. In practice, the accuracy of genomic predictions will depend on the size and structure of reference and training population, the effective population size, the density of marker and the genetic architecture of the traits such as number of loci affecting the traits and distribution of their effects. In this review, we focus on the structure of Hanwoo reference and training population in terms of accuracy of genomic prediction and we then discuss of genetic architecture of intramuscular fat(IMF) and marbling score(MS) to estimate genomic breeding value in real small size of reference population.

• Journal of the Korean Data and Information Science Society
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• 제8권1호
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• pp.71-77
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• 1997

S independent sample 0,1,2, $\cdots$, s-1 (or stages 0,1,2, $\cdots$, s-1) are available from the Raleigh population. Procedure for predicting any order statistic in the $(s+1)^{th}$ sample is developed by obtaining the predictive distribution at stage s. Bounds for the sample size at stage S, in order to have the variance at stage S less than that at stage (s-1), are obtained.