Inverse Gaussian Distribution

Fit, evaluate, and generate random samples from inverse Gaussian distribution

Statistics and Machine Learning Toolbox™ offers multiple ways to work with the inverse Gaussian distribution.

Create an InverseGaussianDistribution object and use InverseGaussianDistribution object functions.
Use the generic distribution functions with the specified distribution name "InverseGaussian" and corresponding parameters.

To learn about the inverse Gaussian distribution, see Inverse Gaussian Distribution.

Functions

`makedist`	Create probability distribution object
`fitdist`	Fit probability distribution object to data
`distributionFitter`	Open Distribution Fitter app

`cdf`	Cumulative distribution function
`gather`	Gather properties of Statistics and Machine Learning Toolbox object from GPU (Since R2020b)
`icdf`	Inverse cumulative distribution function
`iqr`	Interquartile range of probability distribution
`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
`plot`	Plot probability distribution object (Since R2022b)
`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

`cdf`	Cumulative distribution function
`icdf`	Inverse cumulative distribution function
`pdf`	Probability density function
`random`	Random numbers
`mle`	Maximum likelihood estimates

InverseGaussianDistribution Inverse Gaussian probability distribution object

Inverse Gaussian Distribution
Also known as the Wald distribution, the inverse Gaussian is used to model nonnegative positively skewed data.