Difference between revisions of "Manuals/calci/GAMMADIST"

From ZCubes Wiki
Jump to navigation Jump to search
Line 22: Line 22:
 
:<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>.  
 
:<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 <math>\alpha</math> 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.  
+
*For a positive integer <math>n</math>, when <math>\alpha =\frac{n}{2}</math>, <math>\beta = 2</math>, and <math>cu= TRUE</math>, GAMMADIST returns (1 - CHIDIST(x)) with <math>n</math> degrees of freedom.  
*This function shows the result as error when 1.Any one of the argument is non numeric
+
*This function shows the result as error when
2. x<0, alpha<=0 or beta<=0
+
1.Any one of the argument is non numeric
 +
2.<math>x<0, \alpha \le 0 or \beta \le 0</math>
  
 
==Examples==
 
==Examples==

Revision as of 00:24, 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 :

, or

for any positive integer .
  • When alpha is a positive integer, then the distribution is called Erlang distribution.
  • If the shape parameter is held fixed, the resulting one-parameter family of distributions is a natural exponential family.
  • For a positive integer , when , , and , GAMMADIST returns (1 - CHIDIST(x)) with degrees of freedom.
  • This function shows the result as error when
1.Any one of the argument is non numeric
2.

Examples

See Also

References

Bessel Function