• Title/Summary/Keyword: 확률대응사전분포

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Noninformative Priors for the Ratio of Parameters in Inverse Gaussian Distribution (INVERSE GAUSSIAN분포의 모수비에 대한 무정보적 사전분포에 대한 연구)

  • 강상길;김달호;이우동
    • The Korean Journal of Applied Statistics
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    • v.17 no.1
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    • pp.49-60
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    • 2004
  • In this paper, when the observations are distributed as inverse gaussian, we developed the noninformative priors for ratio of the parameters of inverse gaussian distribution. We developed the first order matching prior and proved that the second order matching prior does not exist. It turns out that one-at-a-time reference prior satisfies a first order matching criterion. Some simulation study is performed.

A Statistical Method for Predicting Recurrent Congestion Time in Urban Freeway (도시고속도로 반복정체 시점의 통계학적 분석방법)

  • Han, Yeong-Jun;Son, Bong-Su;Kim, Won-Gil
    • Journal of Korean Society of Transportation
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    • v.24 no.3 s.89
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    • pp.29-37
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    • 2006
  • As a recurrent congestion of urban freeway occurs in almost same time and section, it is possible to manage the congestion effectively by the expectation and advance correspondence. In the existing traffic management system. we have used pattern data to manage a recurrent congestion. But it is not applicable to an urban freeway which kas various traffic circumstance. In this study, the probability by travel speed using a statistical distribution method will be used to predict the probability of recurrent congestion. It is expected that we can get the point of time and the duration of recurrent congestion, and we can devise an effective advance correspondence and a transportation operation.

Improvement in probabilistic drought prediction method using Bayes' theorem (베이즈이론을 이용한 가뭄 확률 전망 기법 고도화)

  • Kim, Daeho;Kim, Young-Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.153-153
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    • 2020
  • 우리나라에선 크고 작은 가뭄 피해가 자주 일어나고 있으며 최근엔 유래 없는 다년가뭄이 발생하면서 가뭄에 대한 경각심이 커지고 있다. 가뭄에 적절하게 대응하여 피해를 경감시키기 위해서는 신뢰도 높은 가뭄 예측이 선행되어야 한다. 이에 본 연구는 앙상블 예측과 베이즈이론(Bayes' theorem)을 수문학적 가뭄지수 중 하나인 SRI(Standardized Runoff Index)에 적용해 가뭄 확률 전망을 실시했으며 이를 EDP(Ensemble Drought Prediction)라고 칭하였다. 국내 8개 댐유역에서 EDP를 생성하고 개선하는 과정은 다음과 같이 진행된다. 우선 TANK모형을 활용한 1개월 선행 유량 예측(Ensemble Streamflow Prediction, ESP)의 결과를 SRI로 변환하여 EDP 확률분포를 생성한다. 그런 다음, EDP를 개선하기 위해 그 기초인 ESP에서 미흡한 토양수분 초기조건을 보완하고자 베이즈이론을 활용했다. APCC(APEC Climate Center)의 위성 관측 SMI(Soil Moisture Index) 자료로 SRI와의 회귀식을 구축, 이를 우도함수로 정의해 사전 EDP 분포를 업데이트한 EDP+ 확률분포를 생성했다. 그 결과, EDP와 EDP+ 모두 심도가 깊은 가뭄을 전망할수록 예측력이 기후학적 예측보다 좋지 않았다. 그럼에도 우도함수로 사용한 회귀식의 정확도가 높을수록 EDP+의 정확도도 향상되는 경향이 나타났으며, 이는 베이즈이론을 사용한다면 가뭄 확률 전망을 개선할 수 있다는 것을 의미하고 있다. 하지만, 확정 전망 정확도는 확률 전망 정확도와는 관계가 없었는데 이는 확정 전망과 확률 전망이 본질적으로 다르기 때문인 것으로 사료된다.

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Bias correction of radar rainfall estimates for improvement of rainfall estimation accuracy in shared river between North and South Korea (남북 공유하천 강수량 추정 정확도 향상을 위한 레이더 강수 편의보정 방안 연구)

  • Son, Chan-Young;Jang, Cheol-Ho;Ban, Woo-Sik;Ahn, Je-Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.300-300
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    • 2019
  • 남북공유하천인 북한강 및 임진강 유역 남측에는 평화의 댐, 군남댐이 치수목적으로 건설되어 운영되고 있으나 북측의 기상 및 수문정보 획득이 불가하여 홍수대응에 불확실성이 높으며 공유하천상류 북측댐 방류패턴에 많은 영향을 받고 있다. 특히 접경지역 남측에 위치한 군남댐은 상류에 있는 황강댐에 비해 저수용량이 작고 우리나라 최북측 수위관측지점(필승교)에서 군남댐까지의 홍수도달시간은 1시간 이내로 예 경보 등 사전 대응에 한계가 있어 북측의 정보가 무엇보다 중요하다. 북측 강우상황 파악 및 위기대응 능력 강화를 위하여 실제 K-water는 기상청 관할 레이더(광덕산)를 활용한 접경지역 댐 유역 강우추정 및 홍수분석 체계를 구축하여 현업에 활용 중이나 실제 관측 강우량 대비 정량적인 차이를 보임에 따라 황강댐 방류 규모 및 군남댐 유입량 예측에 많은 한계가 있다. 따라서, 본 연구에서는 보다 정확한 임진강 상류 북측 강수량 추정을 위하여 기상청 관할 광덕산 레이더에서 얻어지는 군남댐 유역의 추정 강수량(Radar-AWS Rainrate; RAR)에 대하여 통계적 편의보정을 수행하였다. 본 연구에서 적용한 통계적 편의보정기법은 '확률분포형을 활용한 기법', '매개변수적 기법', '비매개변수적 기법' 등 크게 3가지로 구분할 수 있으며 세부적으로 총 11가지 기법을 적용하여 분석을 수행하였다. 분석결과, 일부 기법을 제외하고는 보정 전에 비해 정량적으로 레이더 강수량의 정확도가 향상된 것으로 나타났으며 특히 매개변수적 편의보정기법이 우수한 결과(결정계수: 0.9898)를 보였다. 비매개변수적 편의보정기법은 상대적으로 관측자료가 적어 과거기간에 발생하지 않은 이상치가 발생할 경우 비현실적인 강수로 편의보정되므로 충분한 자료가 축적된 이후 활용가능할 것으로 판단된다. 본 연구의 결과는 북한댐 수문 운영패턴 예측, 접경지역 홍수모의 및 홍수대응 등 치수적인 측면에서 활용도가 높을 것으로 판단된다.

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Bayesian Analysis for Categorical Data with Missing Traits Under a Multivariate Threshold Animal Model (다형질 Threshold 개체모형에서 Missing 기록을 포함한 이산형 자료에 대한 Bayesian 분석)

  • Lee, Deuk-Hwan
    • Journal of Animal Science and Technology
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    • v.44 no.2
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    • pp.151-164
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    • 2002
  • Genetic variance and covariance components of the linear traits and the ordered categorical traits, that are usually observed as dichotomous or polychotomous outcomes, were simultaneously estimated in a multivariate threshold animal model with concepts of arbitrary underlying liability scales with Bayesian inference via Gibbs sampling algorithms. A multivariate threshold animal model in this study can be allowed in any combination of missing traits with assuming correlation among the traits considered. Gibbs sampling algorithms as a hierarchical Bayesian inference were used to get reliable point estimates to which marginal posterior means of parameters were assumed. Main point of this study is that the underlying values for the observations on the categorical traits sampled at previous round of iteration and the observations on the continuous traits can be considered to sample the underlying values for categorical data and continuous data with missing at current cycle (see appendix). This study also showed that the underlying variables for missing categorical data should be generated with taking into account for the correlated traits to satisfy the fully conditional posterior distributions of parameters although some of papers (Wang et al., 1997; VanTassell et al., 1998) presented that only the residual effects of missing traits were generated in same situation. In present study, Gibbs samplers for making the fully Bayesian inferences for unknown parameters of interests are played rolls with methodologies to enable the any combinations of the linear and categorical traits with missing observations. Moreover, two kinds of constraints to guarantee identifiability for the arbitrary underlying variables are shown with keeping the fully conditional posterior distributions of those parameters. Numerical example for a threshold animal model included the maternal and permanent environmental effects on a multiple ordered categorical trait as calving ease, a binary trait as non-return rate, and the other normally distributed trait, birth weight, is provided with simulation study.

A Study on the Factors Affecting Examinee Classification Accuracy under DINA Model : Focused on Examinee Classification Methods (DINA 모형에서 응시생 분류 정확성에 영향을 미치는 요인 탐구 : 응시생 분류방법을 중심으로)

  • Kim, Ji-Hyo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.8
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    • pp.3748-3759
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    • 2013
  • The purpose of this study was to examine the classification accuracies of ML, MAP, and EAP methods under DINA model. For this purpose, this study examined the classification accuracies of the classification methods under the various conditions: the number of attributes, the ability distribution of examinees, and test length. To accomplish this purpose, this study used a simulation method. For the simulation study, data was simulated under the various simulation conditions including the number of attributes (K= 5, 7), the ability distribution of examinees (high, middle, low), and test length (J= 15, 30, 45). Additionally, the percent of agreements between true skill patterns(true ${\alpha}$) and skill patterns estimated by the ML, MAP, and EAP methods were calculated. The summary of the main results of this study is as follows: First, When the number of attributes was 5 and 7, the EAP method showed relatively higher average in the percent of exact agreement than the ML and MAP methods. Second, under the same conditions, as the number of attributes increased, the average percent of exact agreement decreased in ML, MAP, and EAP methods. Third, when the prior distribution of examinees ability was different from low to high under the conditions of the same test length, the EAP method showed relatively higher average in the percent of exact agreement than those of the ML and MAP methods. Fourth, the average percent of exact agreement increased in all methods, ML, MAP, and EAP when the test length increased from 15 to 30 and 45 under the conditions of the same the ability distribution of examinees.

Development of Empirical Fragility Function for High-speed Railway System Using 2004 Niigata Earthquake Case History (2004 니가타 지진 사례 분석을 통한 고속철도 시스템의 지진 취약도 곡선 개발)

  • Yang, Seunghoon;Kwak, Dongyoup
    • Journal of the Korean Geotechnical Society
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    • v.35 no.11
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    • pp.111-119
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    • 2019
  • The high-speed railway system is mainly composed of tunnel, bridge, and viaduct to meet the straightness needed for keeping the high speed up to 400 km/s. Seismic fragility for the high-speed railway infrastructure can be assessed as two ways: one way is studying each element of infrastructure analytically or numerically, but it requires lots of research efforts due to wide range of railway system. On the other hand, empirical method can be used to access the fragility of an entire system efficiently, which requires case history data. In this study, we collect the 2004 MW 6.6 Niigata earthquake case history data to develop empirical seismic fragility function for a railway system. Five types of intensity measures (IMs) and damage levels are assigned to all segments of target system for which the unit length is 200 m. From statistical analysis, probability of exceedance for a certain damage level (DL) is calculated as a function of IM. For those probability data points, log-normal CDF is fitted using MLE method, which forms fragility function for each damage level of exceedance. Evaluating fragility functions calculated, we observe that T=3.0 spectral acceleration (SAT3.0) is superior to other IMs, which has lower standard deviation of log-normal CDF and low error of the fit. This indicates that long-period ground motion has more impacts on railway infrastructure system such as tunnel and bridge. It is observed that when SAT3.0 = 0.1 g, P(DL>1) = 2%, and SAT3.0 = 0.2 g, P(DL>1) = 23.9%.

Comparison of Disaster Vulnerability Analysis and Risk Evaluation of Heat Wave Disasters (폭염재해의 재해취약성분석 및 리스크 평가 비교)

  • Yu-Jeong SEOL;Ho-Yong KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.1
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    • pp.132-144
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    • 2023
  • Recently, the frequency and intensity of heat waves due to the increase in climate change temperature are increasing. Therefore, this study tried to compare the evaluation process and evaluation results of the heat wave disaster evaluation, which is the government's analysis of the heat wave disaster vulnerability and the risk evaluation method recently emphasized by the IPCC. The analysis of climate change disaster vulnerability is evaluated based on manuals and guidelines prepared by the government. Risk evaluation can be evaluated as the product of the possibility of a disaster and its impact, and it is evaluated using the Markov chain Monte Carlo simulation based on Bayesian estimation method, which uses prior information to infer posterior probability. As a result of the analysis, the two evaluation results for Busan Metropolitan City differed slightly in the spatial distribution of areas vulnerable to heat waves. In order to properly evaluate disaster vulnerable areas due to climate change, the process and results of climate change disaster vulnerability analysis and risk assessment must be reviewed, and consider each methodology and countermeasures must be prepared.