Difference between revisions of "Manuals/calci/EXPONDIST"

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  1. x or λ is non-numeric.
 
  1. x or λ is non-numeric.
 
  2. x<0 or λ<=0
 
  2. x<0 or λ<=0
The probability density function  of an exponential distribution is:  
+
The probability density function  of an exponential distribution is:  
 
<math>f(x;λ)=λe^-λx  ,  x>=0 </math>
 
<math>f(x;λ)=λe^-λx  ,  x>=0 </math>
 
             <math> 0        ,  x<0</math>
 
             <math> 0        ,  x<0</math>

Revision as of 23:15, 28 November 2013

EXPONDIST(x,Lambda,cum)


  • is the value of the function
  • is the value of the rate parameter
  • is the logical value like TRUE or FALSE

Description

  • This function gives the exponential distribution. This distribution used to model the time until something happens in the process. *This describes the time between events in a Poisson process i.e., a process in which events occur continuously and independently at a constant average rate.
  • For e.g Time between successive vehicles arrivals at a workshop.
  • In EXPONDIST(x, lambda,cu), xis the value of the function, lambda is called rate parameter and cu(cumulative) is the TRUE or FALSE. *This function will give the cumulative distribution function , when cu is TRUE,otherwise it will give the probability density function , when cu is FALSE.
  • Suppose we are not giving the cu value, by default it will consider the cu value is FALSE.
  • This function will give the error result when
1. x or λ is non-numeric.
2. x<0 or λ<=0

The probability density function of an exponential distribution is: Failed to parse (syntax error): {\displaystyle f(x;λ)=λe^-λx , x>=0 }

           
     or  Failed to parse (syntax error): {\displaystyle f(x;λ)= λe^-λ x .H(x)}

  • where λ is the rate parameter and H(x) is the Heaviside step function
  • This function is valid only on the interval [0,infinity).

The cumulative distribution function is :F(x,λ)={1-e^-λ x, x>=0

                                                  0     ,   x<0        
or                                     :F(x,λ)=1-e^-λ x.H(x). 
  • The mean or expected value of the exponential distribution is: E[x]=1/ λ.
  • The variance of the exponential distribution is:Var[x]=1/ λ^2.