Results 141 to 150 of about 4,368,267 (192)

Bayes Shrinkage Estimators of Weibull Parameters

IEEE Transactions on Reliability, 1985
Shrinking 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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Inferences on the Parameters of the Weibull Distribution

Technometrics, 1969
The problems of estimation and testing hypotheses regarding the parameters in the Weibull distribution are considered in this paper. The following results are given: 1. Exact confidence intervals for the parameters based upon maximum likelihood estimators are presented. 2.
Darrel R. Thoman, Lee J. Bain, Charles E. Antle   +2 more
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Bayesian Estimation of Life Parameters in the Weibull Distribution

Operations Research, 1973
This paper develops a Bayesian analysis of the scale and shape parameters in the Weibull distribution and the corresponding reliability function with respect to the usual life-testing procedures. For the scale parameter θ, Bayesian estimates of θ and reliability are obtained for the uniform, exponential, and inverted gamma prior probability densities.
George C. Canavos, Chris P. Taokas
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Estimation of Weibull parameters

Journal of Materials Science Letters, 1991
where 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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An Addendum to “Linear Estimation of the Weibull Parameters”

Technometrics, 1971
Linear, asymptotically normal and efficient estimators are given for the shape parameter of the two parameter Weibull distribution when the scale parameter is known and for the log of the scale parameter when the shape parameter is known. The weights of the ordered observations and other constants needed for these estimators are readily obtainable from
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Percentile Estimators for the Parameters of the Weibull Distribution

Biometrika, 1971
SUMMARY Large sample estimation of the location and the scale parameter of the Weibull distribution, when the shape parameter is known simultaneously, is considered. Best linear unbiased estimates based on k = 2, 4 and 6 sample quantiles are used. The optimum spacings of the sample quantiles, the coefficients to be used in computing the estimates and ...
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Inference of sampling on Weibull parameter estimation

IEEE Transactions on Dielectrics and Electrical Insulation, 1996
The data usable to evaluate the confidence bounds for the Weibull parameter estimates is provided in broad range of values, in the cases of the "mean squares", "maximum likelihood" and "generalized maximum likelihood" methods. The way to use these results in practice are described in detail.
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Parameter Estimation for the Weibull Distribution

IEEE Transactions on Electrical Insulation, 1977
The 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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Percentiles of Pooled Estimates of Weibull Parameters

IEEE Transactions on Reliability, 1983
In fatigue testing of metals or composite materials under different levels of stress, the underlying distributions are often assumed to be Weibull with a common shape parameter. The problems of estimation and hypothesis tests of the common shape parameter and scale parameters in the Weibull distributions are considered in this paper. The results are: 1)
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On testimating the weibull shape parameter

Communications in Statistics - Simulation and Computation, 1990
A well-known estimator for the shape parameter of a two-parameter Weibull distribution from a failure-censored sample involves a preliminary test of aa null hypothesis concerning the parameter. Efficiency of the resulting testimator varies with the chosen level of significance of the test.
Nimai Kumar Chandra, Arijit Chaudhuri
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