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# Exponential Distribution

Fit, evaluate, and generate random samples from exponential distribution

Statistics and Machine Learning Toolbox™ offers several ways to work with the exponential distribution.

• Create a probability distribution object `ExponentialDistribution` by fitting a probability distribution to sample data or by specifying parameter values. Then, use object functions to evaluate the distribution, generate random numbers, and so on.

• Work with the exponential distribution interactively by using the Distribution Fitter app. You can export an object from the app and use the object functions.

• Use distribution-specific functions with specified distribution parameters. The distribution-specific functions can accept parameters of multiple exponential distributions.

• Use generic distribution functions (`cdf`, `icdf`, `pdf`, `random`) with a specified distribution name (`'Exponential'`) and parameters.

To learn about the exponential distribution, see Exponential Distribution.

## Objects

 `ExponentialDistribution` Exponential probability distribution object

## Apps

 Distribution Fitter Fit probability distributions to data Probability Distribution Function Interactive density and distribution plots

## Functions

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#### Create `ExponentialDistribution` Object

 `makedist` Create probability distribution object `fitdist` Fit probability distribution object to data

#### Work with `ExponentialDistribution` Object

 `cdf` Cumulative distribution function `icdf` Inverse cumulative distribution function `iqr` Interquartile range `mean` Mean of probability distribution `median` Median of probability distribution `negloglik` Negative loglikelihood of probability distribution `paramci` Confidence intervals for probability distribution parameters `pdf` Probability density function `proflik` Profile likelihood function for probability distribution `random` Random numbers `std` Standard deviation of probability distribution `truncate` Truncate probability distribution object `var` Variance of probability distribution
 `expcdf` Exponential cumulative distribution function `exppdf` Exponential probability density function `expinv` Exponential inverse cumulative distribution function `explike` Exponential negative log-likelihood `expstat` Exponential mean and variance `expfit` Exponential parameter estimates `exprnd` Exponential random numbers
 `mle` Maximum likelihood estimates
 `distributionFitter` Open Distribution Fitter app `histfit` Histogram with a distribution fit `qqplot` Quantile-quantile plot `randtool` Interactive random number generation

## Topics

Exponential Distribution

The exponential distribution is special because of its utility in modeling events that occur randomly over time. The main application area is in studies of lifetimes.

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