Difference between revisions of "Manuals/calci/GAMMADIST"

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<div style="font-size:30px">'''GAMMADIST(x,alpha,beta,cu)'''</div><br/>
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<div style="font-size:30px">'''GAMMADIST(x,alpha,beta,cumulative,accuracy)'''</div><br/>
*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.
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*<math>x</math> is the value of the distribution.
 +
*<math>alpha</math> and <math>beta</math> are the value of the parameters.
 +
*<math>cumulative</math> is the logical value like true or false.
 +
*<math>accuracy</math> gives accurate value of the solution.
 +
**GAMMADIST(), returns the gamma distribution.
  
 
==Description==
 
==Description==
*This function gives the value of the gamma distribution.
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*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.
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*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), 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.  
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*This distribution is the Continuous Probability Distribution with two parameters <math>\alpha</math> and <math>\beta</math>.
*If it is TRUE then this function gives the cumulative distribution value or it is FALSE then it gives the probability density function.  
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*In  <math>GAMMADIST(x,alpha,beta,cumulative,accuracy)</math>, <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>cumulative</math> is the logical value like TRUE or FALSE.
*The gamma function is defined by Gamma(t) = integral 0 to infinity  x^{t-1} e^{-x} dx.  
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*If <math>cumulative</math> is TRUE, then this function gives the Cumulative Distribution value and if is FALSE then it gives the Probability Density Function.
*And it is for all complex numbers except the negative integers and zero.  
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*<math>cumulative</math> gives accurate value of the solution.  
*The probability density function of Gamma function using Shape, rate parameters is: f(x; α,ß)=[x^{α-1} e^-{x}]/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.
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*The gamma function is defined by :
*The standard gamma probability density function is: f(x, α)=[x^{α-1} e^-x]/Gamma(α).  
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<math>Gamma(t) = \int\limits_{0}^{\infty}x^{t-1} e^{-x} dx</math>.  
*The  cumulative distribution function of Gamma is F(x;α,ß)=[Gamma(in symbol V)(α, x)]/Gamma(α), or F(x;α,ß)= e^-{x} Summation i=k to infinity 1/i! (x)^i for any positive integer k.  
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*It is for all complex numbers except the negative integers and zero.  
 +
*The Probability Density Function of Gamma function using Shape, rate parameters is:
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<math> f(x; \alpha,\beta)=\frac{x^{\alpha-1} e^{-\frac {x}{\beta}}}{\beta^{\alpha} \Gamma(\alpha)}</math>, for  
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:<math>x, \alpha , \beta > 0 </math>, where <math>e</math> is the natural number(e = 2.71828...),  <math>\alpha</math> is the number of occurrences of an event, and <math>\Gamma(\alpha)</math> is the Gamma function.
 +
*The Standard Gamma Probability Density function is:  
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<math>f(x,\alpha)=\frac{x^{\alpha-1} e^{-x}}{\Gamma(\alpha)}</math>.  
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*The  Cumulative Distribution Function of Gamma is :
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<math>F(x;\alpha,\beta)=\frac{\gamma(\alpha,\frac{x}{\beta})}{\Gamma(\alpha)}</math>, or  
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:<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.
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*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.  
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*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
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*This function shows the result as error when
2. x<0, alpha<=0 or beta<=0
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1.Any one of the argument is non numeric
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2.<math>x<0</math>, <math>\alpha \le 0</math> or <math>\beta \le 0</math>.
 +
 
 +
==ZOS==
 +
*The syntax is to calculate GAMMADIST in ZOS is <math>GAMMADIST(x,alpha,beta,cumulative,accuracy)</math>.
 +
**<math>x</math> is the value of the distribution,
 +
**<math>alpha</math> and <math>beta</math> are the value of the parameters
 +
**<math>cumulative</math> is the logical value like true or false.
 +
**<math>accuracy</math> gives accurate value of the solution.
 +
*For e.g.,GAMMADIST(10.45,2.8,6.4,TRUE,0.9)
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GAMMADIST(10.45,2.8,6.4,FALSE,0.9)
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{{#ev:youtube|l_qRjj8bUdw|280|center|Gamma Distribution}}
 +
 
 
==Examples==
 
==Examples==
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#GAMMADIST(8.15372,5,7,TRUE)=0.006867292
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#GAMMADIST(20.78542,2,6,TRUE)=0.860283293
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#GAMMADIST(20.78542,2,6,FALSE)=0.01806997
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#GAMMADIST(45.6523,9,4,FALSE)=0.019724471
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#GAMMADIST(8.15372,5,7,TRUE,0.5)= 0.00693316259
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#GAMMADIST(8.15372,5,7,TRUE,0.9)=0.0067648564
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 +
==Related Videos==
 +
 +
{{#ev:youtube|SAMTXAAKeug|280|center|GAMMA Distribution}}
  
 
==See Also==
 
==See Also==
Line 25: Line 59:
  
 
==References==
 
==References==
[http://en.wikipedia.org/wiki/Bessel_function| Bessel Function]
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[http://en.wikipedia.org/wiki/Gamma_distribution  Gamma Distribution]
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 +
 
 +
 
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 17:08, 7 August 2018

GAMMADIST(x,alpha,beta,cumulative,accuracy)


  • is the value of the distribution.
  • and are the value of the parameters.
  • is the logical value like true or false.
  • gives accurate value of the solution.
    • GAMMADIST(), returns the gamma distribution.

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 , 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.
  • gives accurate value of the solution.
  • 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.,  or .

ZOS

  • The syntax is to calculate GAMMADIST in ZOS is .
    • is the value of the distribution,
    • and are the value of the parameters
    • is the logical value like true or false.
    • gives accurate value of the solution.
  • For e.g.,GAMMADIST(10.45,2.8,6.4,TRUE,0.9)

GAMMADIST(10.45,2.8,6.4,FALSE,0.9)

Gamma Distribution

Examples

  1. GAMMADIST(8.15372,5,7,TRUE)=0.006867292
  2. GAMMADIST(20.78542,2,6,TRUE)=0.860283293
  3. GAMMADIST(20.78542,2,6,FALSE)=0.01806997
  4. GAMMADIST(45.6523,9,4,FALSE)=0.019724471
  5. GAMMADIST(8.15372,5,7,TRUE,0.5)= 0.00693316259
  6. GAMMADIST(8.15372,5,7,TRUE,0.9)=0.0067648564

Related Videos

GAMMA Distribution

See Also

References

Gamma Distribution