Difference between revisions of "Manuals/calci/GAMMADIST"

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==Examples==
 
==Examples==
  
#EDATE("1/1/1910",2)=Tue Mar 01 1910 00:00:00 GMT +0530 (Indian standard time)
 
#EDATE("5/4/1897",5)=Mon Tue 04 189700:00:00 GMT +0530 (Indian standard time)
 
#EDATE("11/31/1999",3)=Wed Mar 01 200000:00:00 GMT +0530 (Indian standard time)
 
#EDATE("6/6/1979",-2)=Fri Apr 06 197900:00:00 GMT +0530 (Indian standard time)
 
#EDATE("4/15/1950",-6)=Sat  Oct  15  194900:00:00 GMT +0530 (Indian standard time)
 
 
==See Also==
 
==See Also==
 
*[[Manuals/calci/DATE  | DATE ]]
 
*[[Manuals/calci/DATE  | DATE ]]

Revision as of 05:46, 3 December 2013

GAMMADIST(x,alpha,beta,cu)


  • Where 'x' is the value of the distribution,alpha and beta are the value of the parameters and cu 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 α&ß.
  • In GAMMADIST(x,alpha,beta,cu), x is the value of the distribution, alpha is called shape parameter and beta is the rate parameter of the distribution and cu is the logical value like TRUE or FALSE.
  • If it is TRUE then this function gives the cumulative distribution value or it is FALSE then it gives the probability density function.
  • The gamma function is defined by Gamma(t) = integral 0 to infinity x^{t-1} e^{-x} dx.
  • And it is for all complex numbers except the negative integers and zero.
  • The probability density function of Gamma function using Shape, rate parameters is: f(x; α,ß)=[x^{α-1} e^-{x/ß}]/ß^α Gamma(α), for x,α &ß>0, where e is the natural number(e=2.71828...), α is the number of occurrences of an event, and Gamma(α) is the Gamma function.
  • The standard gamma probability density function is: f(x, α)=[x^{α-1} e^-x]/Gamma(α).
  • The cumulative distribution function of Gamma is F(x;α,ß)=[Gamma(in symbol V)(α, x/ß)]/Gamma(α), or F(x;α,ß)= e^-{x/ß} Summation i=k to infinity 1/i! (x/ß)^i for any positive integer k.
  • 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

Examples

See Also

References

Bessel Function