Template:Loglogistic distribution characteristics: Difference between revisions
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(Created page with '====Distribution Characteristics==== For <math>\sigma >1</math> : :• <math>f(T)</math> decreases monotonically and is convex. Mode and mean do not exist. For <math>\sigma…') |
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For <math>\sigma >1</math> : | For <math>\sigma >1</math> : | ||
: | :* <math>f(t)</math> decreases monotonically and is convex. Mode and mean do not exist. | ||
For <math>\sigma =1</math> : | For <math>\sigma =1</math> : | ||
: | :* <math>f(t)</math> decreases monotonically and is convex. Mode and mean do not exist. As <math>t\to 0</math> , <math>f(t)\to \tfrac{1}{\sigma {{e}^{\tfrac{\mu }{\sigma }}}}.</math> | ||
: | :* As <math>t\to 0</math> , <math>\lambda (t)\to \tfrac{1}{\sigma {{e}^{\tfrac{\mu }{\sigma }}}}.</math> | ||
For <math>0<\sigma <1</math> : | For <math>0<\sigma <1</math> : | ||
: | :* The shape of the loglogistic distribution is very similar to that of the lognormal distribution and the Weibull distribution. | ||
: | :* The <math>pdf</math> starts at zero, increases to its mode, and decreases thereafter. | ||
: | :* As <math>\mu </math> increases, while <math>\sigma </math> is kept the same, the <math>pdf</math> gets stretched out to the right and its height decreases, while maintaining its shape. | ||
: | :* As <math>\mu </math> decreases,while <math>\sigma </math> is kept the same, the .. gets pushed in towards the left and its height increases. | ||
: | :* <math>\lambda (t)</math> increases till <math>t={{e}^{\mu +\sigma \ln (\tfrac{1-\sigma }{\sigma })}}</math> and decreases thereafter. <math>\lambda (t)</math> is concave at first, then becomes convex. | ||
[[Image:ldaLLD10.1.gif|thumb|center|400px| ]] | [[Image:ldaLLD10.1.gif|thumb|center|400px| ]] | ||
Revision as of 01:52, 15 February 2012
Distribution Characteristics
For [math]\displaystyle{ \sigma \gt 1 }[/math] :
- [math]\displaystyle{ f(t) }[/math] decreases monotonically and is convex. Mode and mean do not exist.
For [math]\displaystyle{ \sigma =1 }[/math] :
- [math]\displaystyle{ f(t) }[/math] decreases monotonically and is convex. Mode and mean do not exist. As [math]\displaystyle{ t\to 0 }[/math] , [math]\displaystyle{ f(t)\to \tfrac{1}{\sigma {{e}^{\tfrac{\mu }{\sigma }}}}. }[/math]
- As [math]\displaystyle{ t\to 0 }[/math] , [math]\displaystyle{ \lambda (t)\to \tfrac{1}{\sigma {{e}^{\tfrac{\mu }{\sigma }}}}. }[/math]
For [math]\displaystyle{ 0\lt \sigma \lt 1 }[/math] :
- The shape of the loglogistic distribution is very similar to that of the lognormal distribution and the Weibull distribution.
- The [math]\displaystyle{ pdf }[/math] starts at zero, increases to its mode, and decreases thereafter.
- As [math]\displaystyle{ \mu }[/math] increases, while [math]\displaystyle{ \sigma }[/math] is kept the same, the [math]\displaystyle{ pdf }[/math] gets stretched out to the right and its height decreases, while maintaining its shape.
- As [math]\displaystyle{ \mu }[/math] decreases,while [math]\displaystyle{ \sigma }[/math] is kept the same, the .. gets pushed in towards the left and its height increases.
- [math]\displaystyle{ \lambda (t) }[/math] increases till [math]\displaystyle{ t={{e}^{\mu +\sigma \ln (\tfrac{1-\sigma }{\sigma })}} }[/math] and decreases thereafter. [math]\displaystyle{ \lambda (t) }[/math] is concave at first, then becomes convex.
