Template:2ndhalfofWB - Revision history

Lisa Hacker: Redirected page to The Weibull Distribution

2012-08-09T09:52:19Z

Redirected page to The Weibull Distribution

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	[[~~Category: For Deletion~~]]		#REDIRECT [[The Weibull Distribution]]

Lisa Hacker: Replaced content with 'Category: For Deletion'

2012-07-20T12:18:50Z

Replaced content with 'Category: For Deletion'

← Older revision		Revision as of 12:18, 20 July 2012
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	<br>Note that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>		[[Category: For Deletion]]

	~~This analysis method and its characteristics are presented in detail in~~ [[~~Bayesian-Weibull Analysis~~]].

Lisa Hacker at 22:25, 30 March 2012

2012-03-30T22:25:54Z

← Older revision		Revision as of 22:25, 30 March 2012
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	<br>Note that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>		<br>Note that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>

	This analysis method and its characteristics are presented in detail in [[Weibull~~-Bayesian~~ Analysis]].		This analysis method and its characteristics are presented in detail in [[Bayesian-Weibull Analysis]].

Lisa Hacker at 21:41, 30 March 2012

2012-03-30T21:41:30Z

← Older revision		Revision as of 21:41, 30 March 2012
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	<br>~~'''~~Note~~'''~~ that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>		<br>Note that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>

	This analysis method and its characteristics are presented in detail in [[Weibull-Bayesian Analysis]].		This analysis method and its characteristics are presented in detail in [[Weibull-Bayesian Analysis]].

Lisa Hacker at 21:40, 30 March 2012

2012-03-30T21:40:49Z

← Older revision		Revision as of 21:40, 30 March 2012
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	<br>'''Note''' that this is not the same as the so called ~~''WeiBayes'' model. The~~ 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 Bayesian-Weibull feature in Weibull++~~ ~~is actually a true Bayesian 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>		<br>'''Note''' that this is not the same as the so called "WeiBayes model," which is really a one-parameter Weibull distribution that assumes a fixed value (constant) for the shape parameter and solves for the scale parameter. The Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>

	This analysis method and its characteristics are presented in~~ ~~detail in [[Weibull-Bayesian Analysis]].		This analysis method and its characteristics are presented in detail in [[Weibull-Bayesian Analysis]].

Lisa Hacker at 21:30, 30 March 2012

2012-03-30T21:30:54Z

← Older revision		Revision as of 21:30, 30 March 2012
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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++ 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>		<br>'''Note''' that this is not the same as the so called ''WeiBayes'' model. The 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 Bayesian-Weibull feature in Weibull++ is actually a true Bayesian 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>

	~~The Weibull-Bayesian distribution~~ and its characteristics are presented in detail in ~~the~~ [[Weibull-Bayesian Analysis~~]] section in [[The Weibull Distribution\|Chapter 8~~]].		This analysis method and its characteristics are presented in detail in [[Weibull-Bayesian Analysis]].

Kate Racaza at 20:06, 11 March 2012

2012-03-11T20:06:08Z

← Older revision		Revision as of 20:06, 11 March 2012
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	<br>		<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++ 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.
	<br>

	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 detail in the [[Weibull-Bayesian Analysis]] section in [[The Weibull Distribution\|Chapter 8]].

Harry Guo: /* Note */

2012-02-08T21:21:37Z

Note

← Older revision		Revision as of 21:21, 8 February 2012
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	~~====Note====~~
	<br>		<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.		'''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.
	<br>		<br>

	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 more detail in the [[Weibull-Bayesian Analysis]] section in [[The Weibull Distribution \| Chapter 8]].

Nicolette Young at 17:24, 7 February 2012

2012-02-07T17:24:24Z

← Older revision		Revision as of 17:24, 7 February 2012
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	====~~Also~~====		====Note====
	<br>		<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.		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.

Nicolette Young at 17:24, 7 February 2012

2012-02-07T17:24:13Z

← Older revision		Revision as of 17:24, 7 February 2012
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			====Also====
	<br>		<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.		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.