Template:2ndhalfofWB: Difference between revisions

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<br>'''Note''' that this is not the same as the so called WeiBayes model. The so called WeiBayes model is really a one-parameter Weibull distribution. It assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Weibull-Bayesian model in Weibull++&nbsp;is actually a true WeiBayes model and offers an alternative to the one-parameter Weibull by including the variation and uncertainty that is present in the prior estimation of the shape parameter. <br>
'''Note''' that this is not the same as the so called WeiBayes model. The so called WeiBayes model is really a one-parameter Weibull distribution. It assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Weibull-Bayesian model in Weibull++ 7 is actually a true WeiBayes model and offers an alternative to the one-parameter Weibull by including the variation and uncertainty that is present in the prior estimation of the shape parameter.
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The Weibull-Bayesian distribution and its characteristics are presented in more detail in the [[Weibull-Bayesian Analysis]] section in [[The Weibull Distribution | Chapter 8]].
The Weibull-Bayesian distribution and its characteristics are presented in&nbsp;detail in the [[Weibull-Bayesian Analysis]] section in [[The Weibull Distribution|Chapter 8]].

Revision as of 20:06, 11 March 2012


Note that this is not the same as the so called WeiBayes model. The so called WeiBayes model is really a one-parameter Weibull distribution. It assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Weibull-Bayesian model in Weibull++ is actually a true WeiBayes model and offers an alternative to the one-parameter Weibull by including the variation and uncertainty that is present in the prior estimation of the shape parameter.

The Weibull-Bayesian distribution and its characteristics are presented in detail in the Weibull-Bayesian Analysis section in Chapter 8.