• Title/Summary/Keyword: Probability of reference

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On Second Order Probability Matching Criterion in the One-Way Random Effect Model

  • Kim, Dal Ho;Kang, Sang Gil;Lee, Woo Dong
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.29-37
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    • 2001
  • In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

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Noninformative Priors for the Coefficient of Variation in Two Inverse Gaussian Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.429-440
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    • 2008
  • In this paper, we develop the noninformative priors when the parameter of interest is the common coefficient of variation in two inverse Gaussian distributions. We want to develop the first and second order probability matching priors. But we prove that the second order probability matching prior does not exist. It turns out that the one-at-a-time and two group reference priors satisfy the first order matching criterion but Jeffreys' prior does not. The Bayesian credible intervals based on the one-at-a-time reference prior meet the frequentist target coverage probabilities much better than that of Jeffreys' prior. Some simulations are given.

Identification of Prevailing Risk Attitudes in Various Risk Situations (다양한 위험상황에서의 지배적 위험태도의 파악)

  • Kang, Tae-Geon;Cho, Sung-Ku
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.4
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    • pp.437-447
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    • 1999
  • Previous researches on risk attitudes or on the typical utility functions have mostly focused on how the risk attitude of decision maker varies when changes are made in one or two lottery reference points such as consequence domain and magnitude of probability under assumed risk situations represented by simple lotteries. It is, however, very difficult to forecast dominant risk attitudes under risk situations which exhibit a complex combination of many reference points. In this study, twelve risk situations which a decision maker may confront in real decision-making situations were formulated by combining in various ways three reference points, that is, magnitude of probability, consequence domain, and magnitude of gain or loss. Then through a questionnaire dominant risk attitudes under every assumed risk situation were investigated, and the general shape of utility function implied by the experimental results were derived. Results of the present study show that none of the three reference points have dominant effect over the others due to complicated interaction between them, and given the twelve risk situations the observed risk attitude widely varies from strong risk taking to strong risk aversion.

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Bayesian Estimation for the Reliability of a Multicomponent Stress-Strength System Using Noninformative Priors (비정보 사전분포를 이용한 다중 부품 부하-강도체계의 신뢰도에 대한 베이지안 추정)

  • 김병휘;장인홍
    • Proceedings of the Korean Reliability Society Conference
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    • 2000.11a
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    • pp.411-411
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    • 2000
  • Consider the problem of estimating the reliability of a multicomponent stress-strength system which functions if at least r of the k identical components simultaneously function. All stresses and strengths are assumed to be independent random variables with two parameter Weibull distributions. First, we derive reference priors and probability matching priors which are noninformative priors. We next investigate sufficient conditions for propriety of posteriors under reference priors and probability matching priors. Finally, we provide, using these priors, some numerical results for Bayes estimates of the reliability by applying Gibbs sampling technique.

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Noninformative Priors for the Stress-Strength Reliability in the Generalized Exponential Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.467-475
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    • 2011
  • This paper develops the noninformative priors for the stress-strength reliability from one parameter generalized exponential distributions. When this reliability is a parameter of interest, we develop the first, second order matching priors, reference priors in its order of importance in parameters and Jeffreys' prior. We reveal that these probability matching priors are not the alternative coverage probability matching prior or a highest posterior density matching prior, a cumulative distribution function matching prior. In addition, we reveal that the one-at-a-time reference prior and Jeffreys' prior are actually a second order matching prior. We show that the proposed reference prior matches the target coverage probabilities in a frequentist sense through a simulation study and a provided example.

Comparison of Detection Probability for Conventional and Time-Reversal (TR) Radar Systems

  • Yoo, Hyung-Ha;Koh, Il-Suek
    • Journal of electromagnetic engineering and science
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    • v.12 no.1
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    • pp.70-76
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    • 2012
  • We compare the detection probabilities of the time-reversal(TR) detection system and the conventional radar system. The target is assumed to be hidden inside a random medium such as a forest. We propose a TR detection system based on the SAR(Synthetic Aperture Radar) algorithm. Unlike the conventional SAR images, the proposed TR-SAR system has an interesting property. Specifically, the target-related signal components due to the time-reversal refocusing characteristics, as well as some of clutter-related signal components are concentrated at the time-reversal reference point. The remaining clutter-related signal components are scattered around that reference point. In this paper, we model the random media as a collection of point scatterers to avoid unnecessary complexities. We calculate the detection probability of the TR radar system based on the proposed simple random media model.

Study on the fast nearest-neighbor searching classifier using distance approximation (거리 근사를 이용하는 고속 최근 이웃 탐색 분류기에 관한 연구)

  • 이일완;채수익
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.2
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    • pp.71-79
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    • 1997
  • In this paper, we propose a new nearest-neighbor classifier with reduced computational complexity in search process. In the proposed classifier, the classes are divided into two sets: reference and non-reference sets. It reduces computational requriement by approximating the distance between the input and a class iwth the information of distances among the calsses. It calculates only the distance between the input and the reference classes. We convert a given classifier into RCC (reduced computational complexity but smal lincrease in misclassification probability of its corresponding RCC classifier. We designed RCC classifiers for the recognition of digits from the NIST database. We obtained an RCC classifier with 60% reduction in the computational complexity with the cost of 0.5% increase in misclassification probability.

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Probabilistic Forecasting of Seasonal Inflow to Reservoir (계절별 저수지 유입량의 확률예측)

  • Kang, Jaewon
    • Journal of Environmental Science International
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    • v.22 no.8
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    • pp.965-977
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    • 2013
  • Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

NONINFORMATIVE PRIORS FOR PARETO DISTRIBUTION : REGULAR CASE

  • Kim, Dal-Ho;Lee, Woo-Dong;Kang, Sang-Gil
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.05a
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    • pp.27-37
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    • 2003
  • In this paper, we develop noninformative priors for two parameter Pareto distribution. Specially, we derive Jeffrey's prior, probability matching prior and reference prior for the parameter of interest. In our case, the probability matching prior is only a first order and there does not exist a second order matching prior. Some simulation reveals that the matching prior performs better to achieve the coverage probability. And a real example will be given.

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An Web Caching Method based on the Object Reference Probability Distribution Characteristics and the Life Time of Web Object (웹 객체의 참조확률분포특성과 평균수명 기반의 웹 캐싱 기법)

  • Na, Yun-Ji;Ko, Il-Seok
    • Convergence Security Journal
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    • v.6 no.4
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    • pp.91-99
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    • 2006
  • Generally, a study of web caching is conducted on a performance improvement with structural approaches and a new hybrid method using existing methods, and studies on caching method itself. And existing analysis of reference-characteristic are conducted on a history analysis and a preference of users, a view point of data mining by log analysis. In this study, we analyze the reference-characteristic of web object on a view point of a characteristic of probability-distribution and a mean value of lifetime of a web-object. And using this result, we propose the new method for a performance improvement of a web-caching.

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