Lognormal Distribution

Fit, evaluate, generate random samples from lognormal distribution

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

Create a probability distribution object LognormalDistribution 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 lognormal 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 lognormal distributions.
Use generic distribution functions (cdf, icdf, pdf, random) with a specified distribution name ('Lognormal') and parameters.

To learn about the lognormal distribution, see Lognormal Distribution.

Objects

LognormalDistribution Lognormal probability distribution object

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

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

`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

`logncdf`	Lognormal cumulative distribution function
`lognpdf`	Lognormal probability density function
`logninv`	Lognormal inverse cumulative distribution function
`lognlike`	Lognormal negative loglikelihood
`lognstat`	Lognormal mean and variance
`lognfit`	Lognormal parameter estimates
`lognrnd`	Lognormal random numbers