Difference between revisions of "Manuals/calci/EXPONDIST"
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:<math> =0 , x<0</math> | :<math> =0 , x<0</math> | ||
or | or | ||
− | :<math>f(x; | + | :<math>f(x;\lambda)= λe^{-\lambda x} .H(x)</math> |
*where λ is the rate parameter and H(x) is the Heaviside step function | *where λ is the rate parameter and H(x) is the Heaviside step function | ||
*This function is valid only on the interval [0,infinity). | *This function is valid only on the interval [0,infinity). | ||
− | The cumulative distribution function is :F(x, | + | The cumulative distribution function is :<maths>F(x,\lambda)={1-e^{-\lambda x}, x\ge0</maths> |
− | + | <math>0 , x<0 </math> | |
− | or :F(x,λ)=1-e^- | + | or :F(x,λ)=1-e^{-\lambda x}.H(x). |
− | *The mean or expected value of the exponential distribution is: E[x]=1/ | + | *The mean or expected value of the exponential distribution is: <math>E[x]=\frac{1}{ λ}</math> |
− | *The variance of the exponential distribution is:Var[x]=1 | + | *The variance of the exponential distribution is: <math>Var[x]=\frac{1}{\lambda^2}</math>. |
Revision as of 00:21, 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. or is non-numeric. 2. or
The probability density function of an exponential distribution is:
or
- Failed to parse (syntax error): {\displaystyle f(x;\lambda)= λe^{-\lambda 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 :<maths>F(x,\lambda)={1-e^{-\lambda x}, x\ge0</maths>
or :F(x,λ)=1-e^{-\lambda x}.H(x).
- The mean or expected value of the exponential distribution is: Failed to parse (syntax error): {\displaystyle E[x]=\frac{1}{ λ}}
- The variance of the exponential distribution is: .