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Inference on q-Weibull parameters [PDF]
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X. Jia, S. Nadarajah, B. Guo
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Microelectronics Reliability, 1982
Abstract A selective survey of techniques presently suggested for Weibull parameter estimation is provided in a user-oriented approach. The limitations and attractions of graphical estimation procedures are outlined, although the main thrust of the paper is the presentation of efficient statistical procedures for parameter estimation.
Karen Fung, A.K.S. Jardine
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Abstract A selective survey of techniques presently suggested for Weibull parameter estimation is provided in a user-oriented approach. The limitations and attractions of graphical estimation procedures are outlined, although the main thrust of the paper is the presentation of efficient statistical procedures for parameter estimation.
Karen Fung, A.K.S. Jardine
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Bayes Shrinkage Estimators of Weibull Parameters
IEEE Transactions on Reliability, 1985Shrinking an unbiased estimator of a parameter towards a prior value of the parameter has been treated by Thompson, Lemmer, and others. The shrunken estimator is better than the unbiased estimator if true value of the parameter is close to its prior value and is less s-efficient otherwise.
Pandey, M., Upadhyay, S. K.
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Tests of Two-Parameter Exponentiality against Three-Parameter Weibull Alternatives
Technometrics, 1975Two tests are proposed for hypotheses concerning the Weibull shape parameter when the location and scale parameters are unknown. A test based upon maximum likelihood estimation, which relies on existing results for the two-parameter Weibull distribution, is given.
Max Engelhardt, Lee J. Bain
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Weibull-Parameter einiger Maschinenelemente
1990Das Ausfallverhalten von Bauelementen last sich durch entsprechend umfangreiche statistische Auswertungen recht genau ermitteln. Die Auswertungen konnen dabei mit den Ergebnissen eigener Versuche, mit den Daten von Schadensstatistiken oder mit Angaben aus der Literatur erfolgen.
Bernd Bertsche, Gisbert Lechner
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Quality and Reliability Engineering International, 2018
Weibull distribution is one of the most important probability models used in modeling time between events, system reliability, and particle sizes, among others.
Min Gong, A. Mukherjee
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Weibull distribution is one of the most important probability models used in modeling time between events, system reliability, and particle sizes, among others.
Min Gong, A. Mukherjee
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On the determination of Weibull parameters
Journal of Materials Science Letters, 1988La fonction de distribution cumulative de Weibull est utilisee pour decrire la tenacite. On applique les facteurs de poids dans les analyses de regression lineaire d'une equation type et on verifie avec la methode Monte ...
B. Faucher, W. R. Tyson
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Exact Inference on Weibull Parameters With Multiply Type-I Censored Data
IEEE Transactions on Reliability, 2018In reliability engineering, the Weibull distribution and censoring are widely employed. The multiple Type-I censoring is the general form of Type-I censoring and represents that all the test units are terminated at different times.
X. Jia, S. Nadarajah, B. Guo
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Parameter Estimation for the Weibull Distribution
IEEE Transactions on Electrical Insulation, 1977The time to electric breakdown, and the electric field necessary to result in breakdown of solid insulation, seem to be best represented by a Weibull probability distribution. This tutorial paper reviews the graphical method of estimating the parameters of the Weibull distribution.
G. C. Stone, R. G. Van Heeswijk
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Estimation of Weibull parameters
Journal of Materials Science Letters, 1991where P is the fracture probability at stress o, m is the shape parameter or Weibull modulus, o 0 is the scale parameter or characteristic strength and ou is the location parameter or threshold stress. Several methods are available for the determination of the Weibull parameters, and the value of m obtained can vary according to the method employed. In
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