Weibull++ Standard Folio Data 1P-Exponential: Difference between revisions
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{{one parameter | ===The One-Parameter Exponential Distribution=== | ||
The one-parameter exponential <math>pdf</math> is obtained by setting <math>\gamma =0</math>, and is given by: | |||
<math> \begin{align}f(t)= & \lambda {{e}^{-\lambda t}}=\frac{1}{m}{{e}^{-\tfrac{1}{m}t}}, | |||
& t\ge 0, \lambda >0,m>0 | |||
\end{align} | |||
</math> | |||
where: | |||
This distribution requires the knowledge of only one parameter, <math>\lambda </math>, for its application. Some of the characteristics of the one-parameter exponential distribution are [[Appendix: Weibull References| | |||
[19]]]: | |||
#The location parameter, <math>\gamma </math>, is zero. | |||
#The scale parameter is <math>\tfrac{1}{\lambda }=m</math>. | |||
#As <math>\lambda </math> is decreased in value, the distribution is stretched out to the right, and as <math>\lambda </math> is increased, the distribution is pushed toward the origin. | |||
#This distribution has no shape parameter as it has only one shape, i.e. the exponential, and the only parameter it has is the failure rate, <math>\lambda </math>. | |||
#The distribution starts at <math>t=0</math> at the level of <math>f(t=0)=\lambda </math> and decreases thereafter exponentially and monotonically as <math>t</math> increases, and is convex. | |||
#As <math>t\to \infty </math> , <math>f(t)\to 0</math>. | |||
#The <math>pdf</math> can be thought of as a special case of the Weibull <math>pdf</math> with <math>\gamma =0</math> and <math>\beta =1</math>. | |||
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| valign="middle" | [http://www.reliawiki.com/index.php/The_Exponential_Distribution Exponential Distribution] | | valign="middle" | [http://www.reliawiki.com/index.php/The_Exponential_Distribution Exponential Distribution] |
Revision as of 17:12, 8 February 2012
Standard Folio Data 1P-Exponential |
Weibull++ |
The One-Parameter Exponential DistributionThe one-parameter exponential [math]\displaystyle{ pdf }[/math] is obtained by setting [math]\displaystyle{ \gamma =0 }[/math], and is given by: [math]\displaystyle{ \begin{align}f(t)= & \lambda {{e}^{-\lambda t}}=\frac{1}{m}{{e}^{-\tfrac{1}{m}t}}, & t\ge 0, \lambda \gt 0,m\gt 0 \end{align} }[/math] where: This distribution requires the knowledge of only one parameter, [math]\displaystyle{ \lambda }[/math], for its application. Some of the characteristics of the one-parameter exponential distribution are [19]:
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Exponential Distribution |
See Examples... |