• Title/Summary/Keyword: Weibull parameters

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Weibull clutter 에 대한 최대사후확률 일정오경보수신기 (Maximum a posteriori CFAR for weibull clutter)

  • 유경탁;서진헌
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.146-148
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    • 1995
  • A CFAR algorithm for weibull clutter is discussed. The Maximum a posteriori(MAP) estimator for two parameters(skewness and scale) of the weibull clutter is proposed, assuming the probability density function of skewness parameter is known. And proposed MAP estimator is compared with the Maximum likelihood(ML) estimator. Using this MAP estimator, we can design CFAR detector which is shown to have smaller CFAR loss than ML CFAR detector by the statistical simulation method.

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신뢰도 평가에서 제한된 데이터를 이용한 와이블분포 모형화 기법 (A Weibull Model Building Technique for Reliability Assessment with Limited failure Data)

  • 김광원
    • 대한전기학회논문지:전력기술부문A
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    • 제55권3호
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    • pp.109-115
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    • 2006
  • The Weibull distribution is a good candidate for accurate probabilistic model with its rich shape-forming ability and relatively simple CDF(cumulative distribution function). If there are sufficient information to get convincible mean and variance for a probabilistic event, reliable parameters of the Weibull distribution can be determined uniquely. However, sufficient information is not given as usual. There needs more deliberate model building method for that case. This Paper presents an effective parameter estimation technique for Weibull distribution with limited failure data.

석유공급교란에 대한 변화점 분석 및 분포 추정 : 베이지안 접근 (A Change-Point Analysis of Oil Supply Disruption : Bayesian Approach)

  • 박천건;이성수
    • 품질경영학회지
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    • 제35권4호
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    • pp.159-165
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    • 2007
  • Using statistical methods a change-point analysis of oil supply disruption is conducted. The statistical distribution of oil supply disruption is a weibull distribution. The detection of the change-point is applied to Bayesian method and weibull parameters are estimated through Markov chain monte carlo and parameter approach. The statistical approaches to the estimation for the change-point and weibull parameters is implemented with the sets of simulated and real data with small sizes of samples.

와이블분포 하에서 베이지안 기법과 전통적 기법 간의 신뢰도 추정 정확도 비교 (A Comparison of the Reliability Estimation Accuracy between Bayesian Methods and Classical Methods Based on Weibull Distribution)

  • 조형준;임준형;김용수
    • 대한산업공학회지
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    • 제42권4호
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    • pp.256-262
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    • 2016
  • The Weibull is widely used in reliability analysis, and several studies have attempted to improve estimation of the distribution's parameters. least squares estimation (LSE) or Maximum likelihood estimation (MLE) are often used to estimate distribution parameters. However, it has been proven that Bayesian methods are more suitable for small sample sizes than LSE and MLE. In this work, the Weibull parameter estimation accuracy of LSE, MLE, and Bayesian method are compared for sample sets with 3 to 30 data points. The Bayesian method was most accurate for sample sizes under 25, and the accuracy of the Bayesian method was similar to LSE and MLE as the sample size increased.

A new flexible Weibull distribution

  • Park, Sangun;Park, Jihwan;Choi, Youngsik
    • Communications for Statistical Applications and Methods
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    • 제23권5호
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    • pp.399-409
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    • 2016
  • Many of studies have suggested the modifications on Weibull distribution to model the non-monotone hazards. In this paper, we combine two cumulative hazard functions and propose a new modified Weibull distribution function. The newly suggested distribution will be named as a new flexible Weibull distribution. Corresponding hazard function of the proposed distribution shows flexible (monotone or non-monotone) shapes. We study the characteristics of the proposed distribution that includes ageing behavior, moment, and order statistic. We also discuss an estimation method for its parameters. The performance of the proposed distribution is compared with existing modified Weibull distributions using various types of hazard functions. We also use real data example to illustrate the efficiency of the proposed distribution.

Design of Step-Stress Accelerated Life Tests for Weibull Distributions with a Nonconstant Shape Parameter

  • Kim, C. M.;D. S. Bai
    • Journal of the Korean Statistical Society
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    • 제28권4호
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    • pp.415-433
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    • 1999
  • This paper considers the design of step-stress accelerated life tests for the Weibull distribution with a nonconstant shape parameter under Type I censoring. It is assumed that scale and shape parameters are log-linear functions of (possibly transformed) stress and that a cumulative exposure model holds for the effect of changing stress. The asymptotic variance of the maximum likelihood estimator of a stated quantile at design stress is used as an optimality criterion. The optimum three step-stress plans are presented for selected values of design parameters and the effects of errors in pre- estimates of the design parameters are investigated.

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Parameter Estimations in the Complementary Weibull Reliability Model

  • Sarhan Ammar M.;El-Gohary Awad
    • International Journal of Reliability and Applications
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    • 제6권1호
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    • pp.41-51
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    • 2005
  • The Bayes estimators of the parameters included in the complementary Weibull reliability model are obtained. In the process of deriving Bayes estimators, the scale and shape parameters of the complementary Weibull distribution are considered to be independent random variables having prior exponential distributions. The maximum likelihood estimators of the desired parameters are derived. Further, the least square estimators are obtained in closed forms. Simulation study is made using Monte Carlo method to make a comparison among the obtained estimators. The comparison is made by computing the root mean squared errors associated to each point estimation. Based on the numerical study, the Bayes procedure seems better than the maximum likelihood and least square procedures in the sense of having smaller root mean squared errors.

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와이블 모형의 모수 추정에서 분할법의 효율성 (Piecewise Weibull Model with Covariates)

  • 정대현;김주성;원동유
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.295-302
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    • 2000
  • 생존분석에서 널리 이용되고 있는 모형 중 하나인 와이블 모형에 대해 효율적인 모수 추정에 대해 연구하였다. 공변량을 포함하고 있는 와이블 모형의 모수를 추정하기 위하여 전 치료기간을 여러 단계로 나누어 최대우도법을 적용하는 분할법을 소개하였다. 실제의 자료를 적용하여 분할법과 비분할법으로 모수를 추정하여 비교한 결과 분할법의 효율성을 입증하였다.

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Default Bayesian testing for the equality of shape parameters in the inverse Weibull distributions

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1569-1579
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    • 2014
  • This article deals with the problem of testing for the equality of the shape parameters in two inverse Weibull distributions. We propose Bayesian hypothesis testing procedures for the equality of the shape parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Wave Analysis Method for Offshore Wind Power Design Suitable for Suitable for Ulsan Area

  • Woobeom Han;Kanghee Lee;Seungjae Lee
    • 신재생에너지
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    • 제20권2호
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    • pp.2-16
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    • 2024
  • Various loads induced by marine environmental conditions, such as waves, currents, and wind, are crucial for the operation and viability of offshore wind power (OWP) systems. In particular, waves have a significant impact on the stress and fatigue load of offshore structures, and highly reliable design parameters should be derived through extreme value analysis (EVA) techniques. In this study, extreme wave analyses were conducted with various Weibull distribution models to determine the reliable design parameters of an OWP system suitable for the Ulsan area. Forty-three years of long-term hindcast data generated by a numerical wave model were adopted as the analyses data, and the least-squares method was used to estimate the parameters of the distribution function for EVA. The inverse first-order reliability method was employed as the EVA technique. The obtained results were compared among themselves under the assumption that the marginal probability distributions were 2p, 3p, and exponentiated Weibull distributions.