• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.146-148
• /
• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.55 no.3
• /
• pp.109-115
• /
• 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.

• Journal of Korean Society for Quality Management
• /
• v.35 no.4
• /
• pp.159-165
• /
• 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.

• Journal of Korean Institute of Industrial Engineers
• /
• v.42 no.4
• /
• pp.256-262
• /
• 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.

• Communications for Statistical Applications and Methods
• /
• v.23 no.5
• /
• pp.399-409
• /
• 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.

• Journal of the Korean Statistical Society
• /
• v.28 no.4
• /
• pp.415-433
• /
• 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.

• International Journal of Reliability and Applications
• /
• v.6 no.1
• /
• pp.41-51
• /
• 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.

• Journal of the Korean Data and Information Science Society
• /
• v.11 no.2
• /
• pp.295-302
• /
• 2000

We study the efficient method to estimate the parameters for the Weibull model with covariates which occupies an important position in survival analysis. A treatment period may be divided by the stages of treatments under the different treatment arams. The piecewise method is considered to obtain the estimators of the parameters by maximum likelihood method. We explore the real data to show that the piecewise is more efficient than the nonpiecewise to estimate the parameters.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1569-1579
• /
• 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.

• New & Renewable Energy
• /
• v.20 no.2
• /
• pp.2-16
• /
• 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.