Template:Characteristics of the generalized gamma distribution - Revision history

Lisa Hacker: Redirected page to The Generalized Gamma Distribution

2012-08-09T09:35:37Z

Redirected page to The Generalized Gamma Distribution

← Older revision		Revision as of 09:35, 9 August 2012
Line 1:		Line 1:
	~~===Characteristics of the Generalized Gamma Distribution===~~		#REDIRECT [[The_Generalized_Gamma_Distribution]]
	~~As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.~~

	[[~~Image:WB chp12 pdf.png\|center\|250px\|~~ ]]

	~~:• The Weibull distribution is a special case when <math>\lambda =1</math> and:~~

	~~::<math>\begin{align}~~
	~~& \beta = \frac{1}{\sigma } \\~~
	~~& \eta = \ln (\mu )~~
	~~\end{align}</math>~~

	~~:• In this case, the generalized distribution has the same behavior as the Weibull for <math>\sigma >1,</math> <math>\sigma =1,</math> and <math>\sigma <1</math> ( <math>\beta~~
	~~<1,</math> <math>\beta =1,</math> and <math>\beta >1</math> respectively).~~
	~~:• The exponential distribution is a special case when <math>\lambda =1</math> and <math>\sigma =1</math>.~~
	~~:• The lognormal distribution is a special case when <math>\lambda =0</math>.~~
	~~:• The gamma distribution is a special case when <math>\lambda =\sigma </math>.~~

	By allowing <math>\lambda </math> to take negative values, the generalized gamma distribution can be further extended to include additional distributions as special cases. For example, the Fréchet distribution of maxima (also known as a reciprocal Weibull) is a special case when <math>\lambda =-1</math>.

Nicolette Young: /* Characteristics of the Generalized Gamma Distribution */

2012-04-25T21:56:28Z

Characteristics of the Generalized Gamma Distribution

← Older revision		Revision as of 21:56, 25 April 2012
Line 2:		Line 2:
	As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.		As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.

	[[Image:WB chp12 pdf.png\|center\|~~500px~~\| ]]		[[Image:WB chp12 pdf.png\|center\|250px\| ]]

	:• The Weibull distribution is a special case when <math>\lambda =1</math> and:		:• The Weibull distribution is a special case when <math>\lambda =1</math> and:

Nicolette Young: /* Characteristics of the Generalized Gamma Distribution */

2012-03-14T19:04:52Z

Characteristics of the Generalized Gamma Distribution

← Older revision		Revision as of 19:04, 14 March 2012
Line 2:		Line 2:
	As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.		As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.

	[[Image:~~ldagamma10~~.~~1.gif\|thumb~~\|center\|500px\| ]]		[[Image:WB chp12 pdf.png\|center\|500px\| ]]

	:• The Weibull distribution is a special case when <math>\lambda =1</math> and:		:• The Weibull distribution is a special case when <math>\lambda =1</math> and:

Harry Guo: /* Characteristics of the Generalized Gamma Distribution */

2012-02-14T21:47:34Z

Characteristics of the Generalized Gamma Distribution

← Older revision		Revision as of 21:47, 14 February 2012
Line 8:		Line 8:
	::<math>\begin{align}		::<math>\begin{align}
	& \beta = \frac{1}{\sigma } \\		& \beta = \frac{1}{\sigma } \\
	& \eta = & \ln (\mu )		& \eta = \ln (\mu )
	\end{align}</math>		\end{align}</math>

Harry Guo: /* Characteristics of the Generalized Gamma Distribution */

2012-02-14T21:47:24Z

Characteristics of the Generalized Gamma Distribution

← Older revision		Revision as of 21:47, 14 February 2012
Line 7:		Line 7:

	::<math>\begin{align}		::<math>\begin{align}
	& \beta = & \frac{1}{\sigma } \\		& \beta = \frac{1}{\sigma } \\
	& \eta = & \ln (\mu )		& \eta = & \ln (\mu )
	\end{align}</math>		\end{align}</math>

Nicolette Young: Created page with '===Characteristics of the Generalized Gamma Distribution=== As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the…'

2012-01-04T21:10:30Z

Created page with '===Characteristics of the Generalized Gamma Distribution=== As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the…'

New page

===Characteristics of the Generalized Gamma Distribution===
As mentioned previously, the generalized gamma distribution includes other distributions as special cases based on the values of the parameters.

[[Image:ldagamma10.1.gif|thumb|center|500px| ]]

:• The Weibull distribution is a special case when <math>\lambda =1</math> and:

::<math>\begin{align}
& \beta = & \frac{1}{\sigma } \\
& \eta = & \ln (\mu )
\end{align}</math>

:• In this case, the generalized distribution has the same behavior as the Weibull for <math>\sigma >1,</math> <math>\sigma =1,</math> and <math>\sigma <1</math> ( <math>\beta
<1,</math> <math>\beta =1,</math> and <math>\beta >1</math> respectively).
:• The exponential distribution is a special case when <math>\lambda =1</math> and <math>\sigma =1</math>.
:• The lognormal distribution is a special case when <math>\lambda =0</math>.
:• The gamma distribution is a special case when <math>\lambda =\sigma </math>.

By allowing <math>\lambda </math> to take negative values, the generalized gamma distribution can be further extended to include additional distributions as special cases. For example, the Fréchet distribution of maxima (also known as a reciprocal Weibull) is a special case when <math>\lambda =-1</math>.