• Title/Summary/Keyword: Bayesian 모형

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Cancer incidence and mortality estimations in Busan by using spatial multi-level model (공간 다수준 분석을 이용한 부산지역 암발생 및 암사망 추정)

  • Ko, Younggyu;Han, Junhee;Yoon, Taeho;Kim, Changhoon;Noh, Maengseok
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1169-1182
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    • 2016
  • Cancer is a typical cause of death in Korea that becomes a major issue in health care. According to Cause of Death Statistics (2014) by National Statistical Office, SMRs (standardized mortality rates) in Busan were counted as the highest among all cities. In this paper, we used data of Busan Regional Cancer Center to estimate the extent of the cancer incidence rate and cancer mortality rate. The data are considered in small areas of administrative units such as Gu/Dong from years 2003 to 2009. All cancer including four major cancers (stomach cancer, colorectal cancer, lung cancer, liver cancer) have been analyzed. We carried out model selection and parameter estimation using spatial multi-level model incorporating a spatial correlation. For the spatial effects, CAR (conditional autoregressive model) has been assumed.

Urban Flood Risk Assessment Considering Climate Change Using Bayesian Probability Statistics and GIS: A Case Study from Seocho-Gu, Seoul (베이지안 확률통계와 GIS를 연계한 기후변화 도시홍수 리스크 평가: 서울시 서초구를 대상으로)

  • LEE, Sang-Hyeok;KANG, Jung-Eun;PARK, Chang-Sug
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.4
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    • pp.36-51
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    • 2016
  • This study assessed urban flood risk using a Bayesian probability statistical method and GIS incorporating a climate change scenario. Risk is assessed based on a combination of hazard probability and its consequences, the degree of impact. Flood probability was calculated on the basis of a Bayesian model and future flood occurrence likelihoods were estimated using climate change scenario data. The flood impacts include human and property damage. Focusing on Seocho-gu, Seoul, the findings are as follows. Current flood probability is high in areas near rivers, as well as low lying and impervious areas, such as Seocho-dong and Banpo-dong. Flood risk areas are predicted to increase by a multiple of 1.3 from 2030 to 2050. Risk assessment results generally show that human risk is relatively high in high-rise residential zones, whereas property risk is high in commercial zones. The magnitude of property damage risk for 2050 increased by 6.6% compared to 2030. The proposed flood risk assessment method provides detailed spatial results that will contribute to decision making for disaster mitigation.

Estimation of Genetic Parameters via Gibbs Sampler using Animal Model for Economic Traits in Pigs (Gibbs Sampler를 이용한 돼지 주요 경제형질의 유전모수 추정)

  • Cho, K.H.;Kim, M.J.;Kim, I.C.;Jeon, G.J.
    • Journal of Animal Science and Technology
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    • v.50 no.1
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    • pp.19-26
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    • 2008
  • Heritability and genetic correlation for growth traits in Duroc pig breed were estimated using Bayesian method via Gibbs sampling. The data set consisted of 3,526 performance records at National Institute of Animal Science. For estimating those parameters using Gibbs sampling, 5,000 cycles of ‘burn-in’ period were discarded among a total of 55,000 samples. Out of the remaining 50,000 samples, 5,000 estimates by each parameter were retained and used for analyses to avoid any correlation among adjacent samples. The growth traits considered in this study were average daily gain at 30kg(ADG1), average daily gain at 90kg(ADG2), backfat thickness(BF), days to 90kg(D90) and feed conversion ratio(FC). The estimated heritabilities and their standard deviation using Gibbs sampler were 0.43±0.04, 0.49±0.038, 0.31±0.040, 0.48±0.039 and 0.62±0.086, respectively. Genetic correlations were -0.02, -0.13, -0.55 and -0.15 between ADG1 with ADG2, BF, D90 and FC, respectively, 0.16, -0.73, -0.32 between ADG2 with BF, D90 and FC respectively, 0.01, -0.08 between BF with D90, FC, respectively, and 0.23 between D90 with FC.

Predicting Financial Success of a Movie Using Bayesian Choice Model (베이지안 선택 모형을 이용한 영화흥행 예측)

  • Lee Gyeong-Jae;Jang U-Jin
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1851-1856
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    • 2006
  • 영화는 대표적인 경험재로 가치판단이 주관적이고 제품 수명주기가 매우 짧아 예측의 불확실성이 높기 때문에 이를 정량적인 방법으로 모형화하기는 쉽지 않다. 이러한 한계점에도 불구하고 한 영화의 상업적 성공을 예측하는 것은 영화 제작자나 배급사, 극장 등 모든 주체에게 수익과 직결되는 중요한 문제이기 때문에 지금까지 다양한 통계 모형이 제시되었다. 그러나 이들 모형의 대부분은 영화흥행에는 영향을 미치나 측정할 수 없는 효과를 반영하지 못한다거나, 추정 모수의 효과가 모든 영화에 대해서 같다는 동일성 가정으로 인해 영화간 이질성을 고려하지 못하고 있다. 따라서, 본 연구에서는 추정 모수의 사전분포를 모호사전분포로 정의함으로써 변수들의 불확실성을 반영할 수 있고, 영화간 이질성을 고려할 수 있는 베이지안 선택 모형을 제안하였다. 모수의 사후분포는 마코프체인 몬테카를로 기법인 깁스 샘플러를 이용하여 추정하였다. 또한, 감독, 배우, 장르 등의 영화 별 속성 변수뿐만 아니라, 입소문에 의한 영화관람 결정 등의 구전효과와 경쟁영화의 개봉으로 인한 효과를 반영할 수 있는 변수를 추가하여 모형의 정확성을 높였다. 2005년과 2006년 상반기에 상영된 영화를 바탕으로 모형을 구축하고 인공신경망 모형과 비교한 결과, 전체적인 예측 정확도에서는 인공신경망 모형과 비슷한 결과를 보이나 상업적으로 성공한 영화를 예측하는 데에는 베이지안 선택모형이 보다 더 우수한 것으로 나타났다. 또한, 개봉 주의 경쟁심화 정도 및 개봉 첫 주의 스크린 수 등이 영화 흥행에 가장 중요한 변수로 나타났으며, 영화 개봉 전 그 영화에 대한 기대치가 높을수록 흥행 성적 또한 좋음을 알 수 있었다. 배우의 힘 및 계절성, 영화 평점 등은 이질성을 고려하지 않은 전체수준에서는 통계적으로 유의하지 않은 것으로 나타났으나, 그룹 간 이질성을 반영한 모형에서는 어느 정도 흥행한 영화를 만들기 위해서는 고려되어야 할 요소로 나타났다.렇지 않을 경우 적절한 벤치마킹 대상을 도출할 때까지 추가적인 분석과정을 반복한다. 제안한 방법을 통하여 조직은 기술적 생산 가능성 외에도 다양한 조직 운영 관점에서 적절한 벤치마킹 대상을 선정할 수 있으며, 이에 따른 목표를 수립할 수 있을 것으로 기대한다. 또한 더 나아가 global efficiency 관점에서 효율적 조직이 되기 위하여 단계적인 벤치마킹 대상 선정과 이에 따른 목표를 수립하는데도 유용하리라 판단된다.$1.20{\pm}0.37L$, 72시간에 $1.33{\pm}0.33L$로 유의한 차이를 보였으므로(F=6.153, P=0.004), 술 후 폐환기능 회복에 효과가 있다. 4) 실험군과 대조군의 수술 후 노력성 폐활량은 수술 후 72시간에서 실험군이 $1.90{\pm}0.61L$, 대조군이 $1.51{\pm}0.38L$로 유의한 차이를 보였다(t=2.620, P=0.013). 5) 실험군과 대조군의 수술 후 일초 노력성 호기량은 수술 후 24시간에서 $1.33{\pm}0.56L,\;1.00{\ge}0.28L$로 유의한 차이를 보였고(t=2.530, P=0.017), 술 후 72시간에서 $1.72{\pm}0.65L,\;1.33{\pm}0.3L$로 유의한 차이를 보였다(t=2.540, P=0.016). 6) 대상자의 술 후 폐환기능에 영향을 미치는 요인은 성별로 나타났다. 이에 따른 폐환기능의 차이를 보면, 실험군의 술 후 노력성 폐활량이 48시간에 남자($1.78{\pm}0.61L$)가 여자($1.27{\pm}0.45L$)보다 더 높게 나타났으며 (t=2.170, P=0.042), 72시간에도 역시 남자($2.16{\pm}0.56L$)가 여자($1.50{\pm}0.47L$)보다 더

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Estimation of Genetic Parameters for Gestation Length, Wean to First Service, Litter Size and Stillborn Piglets in a Closed Nucleus Swine Breeding Herd (특정 종돈집단의 임신기간, 이유후초종부일, 총산자수 및 사산에 대한 유전모수 추정)

  • Lee, Deukhwan;Son, Jihyun
    • Journal of Animal Science and Technology
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    • v.55 no.5
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    • pp.389-398
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    • 2013
  • This study was conducted to investigate the genetic relationships among four reproductive traits. Data for this study were 7616 records from 1910 Landrace (L) and 10,454 records from 2283 Yorkshire (Y) in a closed nucleus swine herd. Traits considered on this study were gestation length (GL), total number of piglets born (TNB), wean to first service (WFS), and number of stillborn per litter (NSB). Heritabilities and genetic correlations were estimated by using the Bayesian inferences via Gibbs sampling in a four trait linear-threshold repeatability animal mixed model by designating NSB as a categorical trait in the L and Y purebred populations. Effects on the statistical model were considered for parity, contemporary group as fixed and service sire, permanent environmental, animal additive genetic effects as random. Estimates of heritability were 0.21, 0.23, 0.16, and 0.09 for GL, WFS, TNB, and NSB in the L population and 0.35, 0.16, 0.14 and 0.10 for corresponding traits in the Y population, respectively. Genetic correlation for GL was -0.59 and -0.28 with TNB and -0.58 and -0.17 with NSB in the L and Y populations, respectively. The NSB was positively correlated with TNB in the L and Y populations in genetic and environmental aspects. Therefore, the NSB should be taken into account in selecting sows for improving prolificacy of dam line breeding swine stock.

Modeling the Trend of Apartment Market Price in Seoul (서울시 아파트 가격 추세의 모형화)

  • Hwang, Eun-Yeon;Kwon, Yong-Chan;Jang, Dong-Ik;Lee, Jae-Yong;Oh, Hee-Seok
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.173-191
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    • 2008
  • The goal of this paper is analyzing and modeling the trend of apartment market price in Seoul using the dynamic linear model(DLM). We use the market price per pyeong of 30-pyeong-apartment provided by "KB apartment market price database" of Kookmin bank. The data is collected from June $24^{th}$, 2003 to August $28^{th}$, 2006. The inspection of the data reveals that the trend of apartment market price in Seoul can be divided into two groups and we assume that the price is expressed by the common trend of divided groups. We try to estimate the price of apartment by DLM using the Bayesian method.

Dynamic Web Recommendation Method Using Hybrid SOM (하이브리드 SOM을 이용한 동적 웹 정보 추천 기법)

  • Yoon, Kyung-Bae;Park, Chang-Hee
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.471-476
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    • 2004
  • Recently, provides information which is most necessary to the user the research against the web information recommendation system for the Internet shopping mall is actively being advanced. the back which it will drive in the object. In that Dynamic Web Recommendation Method Using SOM (Self-Organizing Feature Maps) has the advantages of speedy execution and simplicity but has the weak points such as the lack of explanation on models and fired weight values for each node of the output layer on the established model. The method proposed in this study solves the lack of explanation using the Bayesian reasoning method. It does not give fixed weight values for each node of the output layer. Instead, the distribution includes weight using Hybrid SOM. This study designs and implements Dynamic Web Recommendation Method Using Hybrid SOM. The result of the existing Web Information recommendation methods has proved that this study's method is an excellent solution.

Effectiveness of Monetary Policy in Korea Due to Time Varying Monetary Policy Stance (거시경제 및 통화정책 기조 변화가 통화정책의 유효성에 미친 영향 분석)

  • Kim, Tae Bong
    • KDI Journal of Economic Policy
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    • v.36 no.3
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    • pp.1-23
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    • 2014
  • This paper has studied the monetary policy in Korea with a time varying VAR model using four key macroeconomic variables. First, inclusion of the exchange rate was a crucial factor in evaluating Korean monetary policy since the monetary policy demonstrated sensitivity to exchange rate movements during the crisis periods of both the Asian financial crisis of 1997 and the global financial crisis of 2008. Second, a specification of the stochastic volatilities in TVP-VAR model is important in explaining excessive movements of all variables in the sample. The overall moderation of variables in 2000s was more or less due to a reduction of the stochastic volatilities but also somewhat due to the macroeconomic fundamental structures captured by impulse response functons. Third, the degree of the monetary policy effectiveness of inflation was mitigated in recent periods but with increased persistence. Lastly, the monetary policy stance towards inflation stabilization has advanced ever since the inflation targeting scheme was adopted. However, there still seems to be a room for improvement in this aspect since the degree of the monetary policy stance towards inflation stabilization was relatively weaker than to output stabilization.

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Discriminant analysis based on a calibration model (Calibration 모형을 이용한 판별분석)

  • 이석훈;박래현;복혜영
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.261-274
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    • 1997
  • Most of the data sets to which the conventional discriminant rules have been applied contain only those which belong to one and only one class among the classes of interest. However the extension of the bivalence to multivlaence like Fuzzy concepts strongly influence the traditional view that an object must belong to only class. Thus the goal of this paper is to develop new discriminant rules which can handle the data each object of which may belong to moer than two classes with certain degrees of belongings. A calibration model is used for the relationship between the feature vector of an object and the degree of belongings and a Bayesian inference is made with the Metropolis algorithm on the degree of belongings when a feature vector of an object whose membership is unknown is given. An evalution criterion is suggested for the rules developed in this paper and comparision study is carried using two training data sets.

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Forecasting Korean CPI Inflation (우리나라 소비자물가상승률 예측)

  • Kang, Kyu Ho;Kim, Jungsung;Shin, Serim
    • Economic Analysis
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    • v.27 no.4
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    • pp.1-42
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    • 2021
  • The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.