Difference between revisions of "Manuals/calci/EXPONDIST"
Jump to navigation
Jump to search
Line 4: | Line 4: | ||
*<math>cu</math> is the logical value like TRUE or FALSE | *<math>cu</math> 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: f(x;λ)={λe^-λx , x>=0 | ||
+ | 0 , x<0 | ||
+ | or f(x;λ)= λ e^-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. | ||
+ | |||
+ | == | ||
EXPONDIST is to model the time between events. | EXPONDIST is to model the time between events. | ||
Revision as of 23:12, 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: f(x;λ)={λe^-λx , x>=0 0 , x<0 or f(x;λ)= λ e^-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.
== EXPONDIST is to model the time between events.
X or Lambda must be a numeric value in this function. Otherwise it shows error.
If x is less than 0, or Lambda less than or equal to zero, EXPONDIST shows error value.
AVEDEV (N1, N2...)
Where N1, N 2 ... are positive integers.
Let’s see an example
EXPONDIST(x, Lambda, cum)
B
0.5
15
=EXPONDIST (B2, B3, TRUE) is 0.9994
=EXPONDIST (0.5, 15, FALSE) is 0.0083