Difference between revisions of "Manuals/calci/EXPONDIST"

From ZCubes Wiki
Jump to navigation Jump to search
Line 15: Line 15:
 
  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}</math>, <math>x\ge0 </math>
+
<math>f(x;λ)=λe^{-λx}</math>,<math>x\ge0 </math>
 
:<math> =0  ,  x<0</math>
 
:<math> =0  ,  x<0</math>
 
or   
 
or   

Revision as of 00:25, 29 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}} ,

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

                                     
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.