• Title/Summary/Keyword: Risk Estimation

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Development of Estimation Technique for Rice Yield Reduction by Inundation Damage (침수피해에 의한 벼 감수량 추정기법 개발)

  • Park , Jong-Min;Kim , Sang-Min;Seong, Chung-Hyun;Park, Seung-Woo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.5
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    • pp.89-98
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    • 2004
  • The amount of rice yield reduction due to inundation should be estimated to analyse economic efficiency of the farmland drainage improvement projects because those projects are generally promoted to mitigate flood inundation damage to rice in Korea. Estimation of rice yield reduction will also provide information on the flood risk performance to farmers. This study presented the relationships between inundated durations and rice yield reduction rates for different rice growth stages from the observed data collected from 1966 to 2000 in Korea, and developed the rice yield reduction estimation model (RYREM). RYREM was applied to the test watershed for estimating the rice yield reduction rates and the amount of expected average annual rice yield reduction by the rainfalls with 48 hours duration, 10, 20, 50, 100, 200 years return periods.

Multistage Point and Confidence Interval Estimation of the Shape Parameter of Pareto Distribution

  • Hamdy, H.I.;Son, M.S.;Gharraph, M.K.;Rashad, A.M.
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.1069-1086
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    • 2003
  • This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

Effective Computation for Odds Ratio Estimation in Nonparametric Logistic Regression

  • Kim, Young-Ju
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.713-722
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    • 2009
  • The estimation of odds ratio and corresponding confidence intervals for case-control data have been done by traditional generalized linear models which assumed that the logarithm of odds ratio is linearly related to risk factors. We adapt a lower-dimensional approximation of Gu and Kim (2002) to provide a faster computation in nonparametric method for the estimation of odds ratio by allowing flexibility of the estimating function and its Bayesian confidence interval under the Bayes model for the lower-dimensional approximations. Simulation studies showed that taking larger samples with the lower-dimensional approximations help to improve the smoothing spline estimates of odds ratio in this settings. The proposed method can be used to analyze case-control data in medical studies.

Assessment of Maximum Use Levels and Estimation of Theoretical Maximum Daily Intake for 9 Food Additives in Korea by the Budget Method (Budget 방법론에 의한 한국의 식품첨가물 사용기준평가 및 식품첨가물 9종에 대한 이론적 최대섭취량의 추정)

  • 윤혜정;이미경;이창희;이종옥;이철원
    • Journal of Food Hygiene and Safety
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    • v.14 no.2
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    • pp.186-194
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    • 1999
  • The Budget method used currently in Codex for estimation of use levels of food additives was investigated and the specific approach that can be applicable for Koreans has been proposed. Theoretical maximum daily intakes(TMDIs) of benzoate, $\rho$-hydroxybenzoic acid ester, butylated hydroxyanisole(BHA), butylated hydroxytoluene (BHT), t-butylhydroquinone(TBHQ), nitrite, nitrate, sorbate, and sulfite were estimated and compared with corresponding acceptable daily intakes(ADIs). Additives requiring further precise evaluation were screened. TMDIs of benzoate, BHA, BHT, TBHQ, nitrite, and sulfite exceeded ADIs. On the other hand, it is appeared that TMDIs of $\rho$-hydroxybenzoic acid ester, nitrate, and sorbate were below ADIs. It is expected that the Budget method may be used as one approach for the estimation of use level and risk assessment.

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Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks(III)-Model Parameter Identification- (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구 (III)-모델 매개변수 분석-)

  • 이인모;박경호
    • Geotechnical Engineering
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    • v.8 no.4
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    • pp.41-50
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    • 1992
  • In general, the conceptual lumped-parameter groundwater flow model to predict the groundwater fluctuations in hillside slopes has unknown model parameters to be estimated from the known input -output data. The purpose of this study is to estimate the optimal model parameters of the groundwater flow model developed by authors. The Mazilnum A Posteriori( MAP) estimation method is utilized for this purpose and it is applied to a site which shows the typical landslide in Korea. The result of application shows tllat the 반AP estimation method can estimate the unknown parameters properly well. The groundwater model developed along with estimation technique applied in this paper will be used for assessing risk of landslides.

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Risk-based Test Case/Test Set Value Estimation Model (리스크 기반 테스트 케이스/테스트 세트 가치 추정 모델)

  • Kwon, Won-Il;Kim, Jong-Ku;Kwon, Ho-Yeol
    • Journal of Industrial Technology
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    • v.32 no.A
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    • pp.125-128
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    • 2012
  • In this paper, we proposed a prioritization method of test cases using a value estimation model of test sets, that are key elements for highly effective software testings as well as involve a large cost factor in software developments and maintenances. Based on previous studies, our idea includes introducing some practical factors of the test case prioritization which critically influence the value of a test case: Relative values of test sets before and after the test running, Average value of these two relative values, Severity of the defect, Risks that are covered, Frequency of use, Change related values, Systematic elicitations, etc. Finally we discussed the usefulness and the expected effects of the proposed scheme.

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Regression Technique-based Productivity Estimation conducting Construction Delay Factor Analysis on Interior Works in High-rise Building Construction (공기지연요소분석을 이용한 회귀분석 기반 초고층 내부공사의 생산성 예측)

  • Kim, Hyun-mi;Kim, Tae-Hyung;Shin, Young-Keun;Kim, Young-Suk;Han, Seungwoo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2011.05a
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    • pp.191-192
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    • 2011
  • The construction projects contain a lot of variables and risk affecting productivity. The duration of the project must be recognized important as for quality, unit cost and safety. There is need for improving work efficiency by investigating relationship of works to prevent delay. This study focuses on analysing the delay factors of steel staircase system to suggest regression model that enables construction productivity estimation. The position of the observers and construction delay factors were expressed by the independent variable of the regression model and productivity was expressed by a dependent variable. This paper suggests quantitative productivity and it is expected that will be helpful estimating application in construction new technologies.

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Cluster Sampling in Sampling Inspection: Bayes Estimation

  • Juyoung Lee
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.107-116
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    • 1999
  • We propose a sample design which minimize Bayes risk for cluster smpling in sampling inspection. We treat a pilot sample and an additional sample size as random variable. In addition we compute an appropriate cluster size for handling over-dispersion.

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A Test on the Volatility Feedback Hypothesis in the Emerging Stock Market (신흥주식시장에서의 변동성반응가설 검정)

  • Kim, Byoung-Joon
    • The Korean Journal of Financial Management
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    • v.26 no.4
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    • pp.191-234
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    • 2009
  • This study examined on the volatility feedback hypothesis through the use of threshold GARCH-in-Mean (GJR-GARCH-M) model developed by Glosten, Jaganathan, and Runkle (1993) in the stock markets of 14 emerging countries during the period of January, 1996 to May, 2009. On this study, I found successful evidences which can support the volatility feedback hypothesis through the following three estimation procedures. First, I found relatively strong positive relationship between the expected market risk premiums and their conditional standard deviations from the GARCH-M model in the basis of daily return on each representative stock market index, which is appropriate to investors' risk-averse preferences. Second, I can also identify the significant asymmetric time-varying volatility originated from the investors' differentiated reactions toward the unexpected market shocks by applying the GJR-GARCH-M model and further find the lasting positive risk aversion coefficient estimators. Third, I derived the negative signs of the regression coefficient of unpredicted volatility on the stock market return by re-applying the GJR-GARCH-M model after I controlled the positive effect of predicted volatility through including the conditional standard deviations from the previous GARCH-M model estimation as an independent explanatory variable in the re-applied new GJR-GARCH-M model. With these consecutive results, the volatility feedback effect was successfully tested to be effective also in the various emerging stock markets, although the leverage hypothesis turned out to be insufficient to be applied to another source of explaining the negative relationship between the unexpected volatility and the ex-post stock market return in the emerging countries in general.

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