Gamma Distribution

Fit, evaluate, and generate random samples from gamma distribution

Functions

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

`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

`gamcdf`	Gamma cumulative distribution function
`gampdf`	Gamma probability density function
`gaminv`	Gamma inverse cumulative distribution function
`gamlike`	Gamma negative log-likelihood
`gamstat`	Gamma mean and variance
`gamfit`	Gamma parameter estimates
`gamrnd`	Gamma random numbers
`randg`	Gamma random numbers with unit scale

Objects

GammaDistribution Gamma probability distribution object

Topics

Gamma Distribution

The gamma distribution models sums of exponentially distributed random variables.

Statistics and Machine Learning Toolbox Documentation

Support

Mastering Machine Learning: A Step-by-Step Guide with MATLAB

Mastering Machine Learning: A Step-by-Step Guide with MATLAB