• Title/Summary/Keyword: new better than used distributions

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A Goodness of Fit Approach for Testing NBUFR (NWUFR) and NBAFR (NWAFR) Properties

  • Mahmoud, M.A.W.;Alim, N.A. Abdul
    • International Journal of Reliability and Applications
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    • v.9 no.2
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    • pp.125-140
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    • 2008
  • The new better than used failure rate (NBUFR), Abouammoh and Ahmed (1988), and new better than average failure rate (NBAFR) Loh (1984) classes of life distributions, have been considered in the literature as natural weakenings of NBU (NWU) property. The paper considers testing exponentiality against strictly NBUFR (NBAFR) alternatives, or their duals, based on goodness of fit approach that is possible in life testing problems and that it results in simpler procedures that are asymptotically equivalent or better than standard ones. They may also have superior finite sample behavior. The asymptotic normality are proved. Powers, Pitman asymptotic efficiency and critical points are computed. Dealing with censored data case also studied. Practical applications of our tests in the medical sciences are present.

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On NBUL class at specific age

  • Mahmoud, M.A.W.;Moshref, M.E.;Gadallah, A.M.
    • International Journal of Reliability and Applications
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    • v.15 no.1
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    • pp.11-22
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    • 2014
  • New classes of life distributions called new better (worse) than used at age $t_0$ in Laplace transform order, NBUL- $t_0$(NWUL - $t_0$) are introduced. For the classes NBUL - $t_0$(NWUL - $t_0$), preservation under convolution, mixture, mixing and the homogeneous Poisson shock model are studied. In the sequel, we obtain a test for $H_0$ : F is exponential versus $H_1$ : F is NBUL - $t_0$ and not exponential. The critical values and the powers of this test are calculated to assess the performance of the test. It is shown that the proposed test has high efficiencies for some commonly used distributions in reliability. Sets of real data are used as examples to elucidate the use of the proposed test for practical problems.

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Testing Harmonic Used Better than Aged in Expectation in Upper Tail(HUBAEUT) Class of Life Distributions Using Kernel Method

  • Abu-Youssef, S.E.;Al-nachawati, H.
    • International Journal of Reliability and Applications
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    • v.7 no.2
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    • pp.89-99
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    • 2006
  • A new classes of life distribution, namely harmonic used better than aged in expectation in upper tail (HUBAEUT) is introduced. Testing exponentiality against this class is investigated using kernel method. The limiting null and nonnull distribution of the test statistics is normal and the null variance is calculated exactly. Selected critical values are tabulated for sample sizes of 5(1)40. Power of the test are estimated by simulation. the efficacies of the test statistics used for testing against HUBAEUT are calculated for som common alternatives and are compared to some other procedures. It is shown that proposed test is simple, has high relative efficiency and power for some commonly used alternatives. The set of real data are used as an examples to elucidate the use of the proposed test statistics for practical reliability.

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Optimal Design of Accelerated Life Tests under Model Uncertainty (불확정 모형하에서 가속수명시험의 최적 설계)

  • 서순근;하천수;김갑석
    • Journal of Korean Society for Quality Management
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    • v.29 no.3
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    • pp.49-65
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    • 2001
  • This paper presents new compromise ALT plan which is applied to situations that true relationship between stress and parameters is not known exactly. The assumed failure distribution of this study is one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. The method of applying the stress is constant, and the censoring mechanism is Type I censoring. Compared with existing compromise plans under true simple linear model in terms of statistical efficiency, the efficiency of new compromise plan is better than the corresponding other compromise ones in most cases. For case when true model is quadratic, this plan can be used without any severe loss in statistical efficiency. The proposed new compromise ALT plan is illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

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A generalized Hollander-Proschan test for NBUE alternative based on U-statistics approach

  • Hassan, M.KH.
    • International Journal of Reliability and Applications
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    • v.16 no.2
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    • pp.113-122
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    • 2015
  • In this paper, we introduce U-statistics approach to generalized Hollander-Proschan test for new better than used (NBUE) alternative. We prove, the proposed test is equivalent to test was introduced by Anis and Mitra (2011) and includes test was introduced by Hollander Proschan (1975). Also, the asymptotic properties are studied. The powers of our test are estimated. The Pitman asymptotic efficiencies of proposed test are also calculated. Finally, the test is applied to some real data.

On NBUmgf class at specific age

  • Gadallah, A.M.
    • International Journal of Reliability and Applications
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    • v.17 no.2
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    • pp.107-119
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    • 2016
  • A new concept of aging classes namely new better (worse) than used at age $t_0$ in moment generating function order, $NBU_{mgf}-t_0$ ($NWU_{mgf}-t_0$) is introduced. For the classes $NBU_{mgf}-t_0$ ($NWU_{mgf}-t_0$), preservation under convolution, mixture, mixing and the homogeneous Poisson shock model are studied. In the sequel, nonparametric test is proposed, the asymptotic normality of the class is established and the asymptotic null variance is estimated. The percentiles and powers of this test are tabulated. The asymptotic efficiencies for some alternatives distributions are derived. Finally sets of real data are used as examples to elucidate the use of the proposed test in practical application.

The Gringorten estimator revisited

  • Cook, Nicholas John;Harris, Raymond Ian
    • Wind and Structures
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    • v.16 no.4
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    • pp.355-372
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    • 2013
  • The Gringorten estimator has been extensively used in extreme value analysis of wind speed records to obtain unbiased estimates of design wind speeds. This paper reviews the derivation of the Gringorten estimator for the mean plotting position of extremes drawn from parents of the exponential type and demonstrates how it eliminates most of the bias caused by the classical Weibull estimator. It is shown that the coefficients in the Gringorten estimator are the asymptotic values for infinite sample sizes, whereas the estimator is most often used for small sample sizes. The principles used by Gringorten are used to derive a new Consistent Linear Unbiased Estimator (CLUE) for the mean plotting positions for the Fisher Tippett Type 1, Exponential and Weibull distributions and for the associated standard deviations. Analytical and Bootstrap methods are used to calibrate the bias error in each of the estimators and to show that the CLUE are accurate to better than 1%.

Direction Estimation of Multiple Sound Sources Using Circular Probability Distributions (순환 확률분포를 이용한 다중 음원 방향 추정)

  • Nam, Seung-Hyon;Kim, Yong-Hoh
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.6
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    • pp.308-314
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    • 2011
  • This paper presents techniques for estimating directions of multiple sound sources ranging from $0^{\circ}$ to $360^{\circ}$ using circular probability distributions having a periodic property. Phase differences containing direction information of sources can be modeled as mixtures of multiple probability distributions and source directions can be estimated by maximizing log-likelihood functions. Although the von Mises distribution is widely used for analyzing this kind of periodic data, we define a new class of circular probability distributions from Gaussian and Laplacian distributions by adopting a modulo operation to have $2{\pi}$-periodicity. Direction estimation with these circular probability distributions is done by implementing corresponding EM (Expectation-Maximization) algorithms. Simulation results in various reverberant environments confirm that Laplacian distribution provides better performance than von Mises and Gaussian distributions.

A Method to Improve the Performance of Adaboost Algorithm by Using Mixed Weak Classifier (혼합 약한 분류기를 이용한 AdaBoost 알고리즘의 성능 개선 방법)

  • Kim, Jeong-Hyun;Teng, Zhu;Kim, Jin-Young;Kang, Dong-Joong
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.457-464
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    • 2009
  • The weak classifier of AdaBoost algorithm is a central classification element that uses a single criterion separating positive and negative learning candidates. Finding the best criterion to separate two feature distributions influences learning capacity of the algorithm. A common way to classify the distributions is to use the mean value of the features. However, positive and negative distributions of Haar-like feature as an image descriptor are hard to classify by a single threshold. The poor classification ability of the single threshold also increases the number of boosting operations, and finally results in a poor classifier. This paper proposes a weak classifier that uses multiple criterions by adding a probabilistic criterion of the positive candidate distribution with the conventional mean classifier: the positive distribution has low variation and the values are closer to the mean while the negative distribution has large variation and values are widely spread. The difference in the variance for the positive and negative distributions is used as an additional criterion. In the learning procedure, we use a new classifier that provides a better classifier between them by selective switching between the mean and standard deviation. We call this new type of combined classifier the "Mixed Weak Classifier". The proposed weak classifier is more robust than the mean classifier alone and decreases the number of boosting operations to be converged.

Stochastic Properties of Life Distribution with Increasing Tail Failure Rate and Nonparametric Testing Procedure

  • Lim, Jae-Hak;Park, Dong Ho
    • Journal of Applied Reliability
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    • v.18 no.3
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    • pp.220-228
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    • 2018
  • Purpose: The purpose of this study is to investigate the tail behavior of the life distribution which exhibits an increasing failure rate or other positive aging effects after a certain time point. Methods: We characterize the tail behavior of the life distribution with regard to certain reliability measures such as failure rate, mean residual life and reliability function and derive several stochastic properties regarding such life distributions. Also, utilizing an L-statistic and its asymptotic normality, we propose new nonparametric testing procedures which verify if the life distribution has an increasing tail failure rate. Results: We propose the IFR-Tail (Increasing Failure Rate in Tail), DMRL-Tail (Decreasing Mean Residual Life in Tail) and NBU-Tail (New Better than Used in Tail) classes, all of which represent the tail behavior of the life distribution. And we discuss some stochastic properties of these proposed classes. Also, we develop a new nonparametric test procedure for detecting the IFR-Tail class and discuss its relative efficiency to explore the power of the test. Conclusion: The results of our research could be utilized in the study of wide range of applications including the maintenance and warranty policy of the second-hand system.