Exponential probability density function

`Y = exppdf(X,mu)`

`Y = exppdf(X,mu)`

returns
the pdf of the exponential distribution with mean parameter `mu`

,
evaluated at the values in `X`

. `X`

and `mu`

can
be vectors, matrices, or multidimensional arrays that have the same
size. A scalar input is expanded to a constant array with the same
dimensions as the other input. The parameters in `mu`

must
be positive.

The exponential pdf is

$$y=f(x|\mu )=\frac{1}{\mu}{e}^{\frac{-x}{\mu}}$$

The exponential pdf is the gamma pdf with its first parameter equal to 1.

The exponential distribution is appropriate for modeling waiting times when the probability of waiting an additional period of time is independent of how long you have already waited. For example, the probability that a light bulb will burn out in its next minute of use is relatively independent of how many minutes it has already burned.

y = exppdf(5,1:5) y = 0.0067 0.0410 0.0630 0.0716 0.0736 y = exppdf(1:5,1:5) y = 0.3679 0.1839 0.1226 0.0920 0.0736

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