Difference between revisions of "Manuals/calci/GAMMADIST"
Jump to navigation
Jump to search
Line 6: | Line 6: | ||
==Description== | ==Description== | ||
*This function gives the value of the Gamma Distribution. | *This function gives the value of the Gamma Distribution. | ||
− | *The Gamma Distribution can be used in a queuing models like, the amount of rainfall accumulated in a reservoir. *This distribution is the Continuous Probability Distribution with two parameters <math>\alpha</math> and <math>\beta</math>. | + | *The Gamma Distribution can be used in a queuing models like, the amount of rainfall accumulated in a reservoir. |
− | *In GAMMADIST(x,alpha,beta,cu), <math>x</math> is the value of the distribution, <math>\alpha</math> is called shape parameter and <math>beta</math> is the rate parameter of the distribution and <math>cu</math> is the logical value like TRUE or FALSE. | + | *This distribution is the Continuous Probability Distribution with two parameters <math>\alpha</math> and <math>\beta</math>. |
+ | *In GAMMADIST(x,alpha,beta,cu), <math>x</math> is the value of the distribution, <math>\alpha</math> is called shape parameter and <math>\beta</math> is the rate parameter of the distribution and <math>cu</math> is the logical value like TRUE or FALSE. | ||
*If <math>cu</math> is TRUE, then this function gives the Cumulative Distribution value and if is FALSE then it gives the Probability Density Function. | *If <math>cu</math> is TRUE, then this function gives the Cumulative Distribution value and if is FALSE then it gives the Probability Density Function. | ||
*The gamma function is defined by : | *The gamma function is defined by : | ||
Line 17: | Line 18: | ||
*The standard Gamma Probability Density function is: | *The standard Gamma Probability Density function is: | ||
<math>f(x, \alpha)=\frac{x^{\alpha-1} e^{-x}}{Gamma(\alpha)}</math>. | <math>f(x, \alpha)=\frac{x^{\alpha-1} e^{-x}}{Gamma(\alpha)}</math>. | ||
− | *The Cumulative Distribution Function of Gamma is <math>F(x;\alpha,\beta)=[\gamma(\alpha,\frac{x}{\beta}}{Gamma(\alpha)}</math>, or <math>F(x;\alpha,\beta)= e^- | + | *The Cumulative Distribution Function of Gamma is <math>F(x;\alpha,\beta)=[\gamma(\alpha,\frac{x}{\beta}}{Gamma(\alpha)}</math>, or <math>F(x;\alpha,\beta)= e^{-\frac {x}{\beta}} \sum_{i=k}^{\infty} \frac{1}{i!} (\frac{x}{\beta})^i</math> for any positive integer <math>k</math>. |
*When alpha is a positive integer, then the distribution is called Erlang distribution. | *When alpha is a positive integer, then the distribution is called Erlang distribution. | ||
*If the shape parameter α is held fixed, the resulting one-parameter family of distributions is a natural exponential family. | *If the shape parameter α is held fixed, the resulting one-parameter family of distributions is a natural exponential family. |
Revision as of 00:09, 4 December 2013
GAMMADIST(x,alpha,beta,cu)
- is the value of the distribution,
- and are the value of the parameters
- is the logical value like true or false.
Description
- This function gives the value of the Gamma Distribution.
- The Gamma Distribution can be used in a queuing models like, the amount of rainfall accumulated in a reservoir.
- This distribution is the Continuous Probability Distribution with two parameters and .
- In GAMMADIST(x,alpha,beta,cu), is the value of the distribution, is called shape parameter and is the rate parameter of the distribution and is the logical value like TRUE or FALSE.
- If is TRUE, then this function gives the Cumulative Distribution value and if is FALSE then it gives the Probability Density Function.
- The gamma function is defined by :
.
- It is for all complex numbers except the negative integers and zero.
- The Probability Density Function of Gamma function using Shape, rate parameters is:
, for
- , where is the natural number(e = 2.71828...), is the number of occurrences of an event, and is the Gamma function.
- The standard Gamma Probability Density function is:
.
- The Cumulative Distribution Function of Gamma is Failed to parse (syntax error): {\displaystyle F(x;\alpha,\beta)=[\gamma(\alpha,\frac{x}{\beta}}{Gamma(\alpha)}} , or for any positive integer .
- When alpha is a positive integer, then the distribution is called Erlang distribution.
- If the shape parameter α is held fixed, the resulting one-parameter family of distributions is a natural exponential family.
- For a positive integer n, when alpha = n/2, beta = 2, and cu= TRUE, GAMMADIST returns (1 - CHIDIST(x)) with n degrees of freedom.
- This function shows the result as error when 1.Any one of the argument is non numeric
2. x<0, alpha<=0 or beta<=0