Beta Distribution

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

Create a BetaDistribution object and use BetaDistribution object functions.
Use distribution-specific functions with specified distribution parameters. The functions can accept parameters of multiple beta distributions.
Use the generic distribution functions with the specified distribution name "Beta" and corresponding parameters.

To learn about the beta distribution, see Beta Distribution.

Functions

Create BetaDistribution Object

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

Work with BetaDistribution Object

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

Distribution-Specific Functions

betacdf	Beta cumulative distribution function
betapdf	Beta probability density function
betainv	Beta inverse cumulative distribution function
betalike	Beta negative log-likelihood
betastat	Beta mean and variance
betafit	Beta parameter estimates
betarnd	Beta random numbers

Generic Functions

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