Generates log-normal distribution parameter estimates and confidence intervals.

Syntax

Mean, Std, MeanCI, StdCI = LogNormFit(Points)

Argument

Name

Description

Points

A vector of positive data points.

Outputs

Name

Description

Mean

Estimate of the mean of the log of the distribution. A scalar.

Std

Estimate of the standard deviation of the log of the distribution. A positive scalar.

MeanCI

95% confidence interval of the estimate of Mu. A two element row vector containing the lower and upper bounds of the confidence interval.

StdCI

95% confidence interval of the estimate of Sigma. A two element row vector containing the lower and upper bounds of the confidence interval.

Example

For a given data set, find Mu, sigma and the confidence intervals, assuming a log-normal distribution.

Syntax

mu, sigma, muCI, sigmaCI = LogNormFit(data)

Results

Mu is the maximum likelihood estimate of the mean of the log of the distribution.

sigma is the maximum likelihood estimate of the standard deviation of the log of the distribution.

MuCI is a two element vector, with MuCI(1) being the lower and MuCI(2) being the upper interval of the 95% confidence interval of the Mean.

sigmaCI is a two element vector, with sigmaCI(1) being the lower and sigmaCI(2) being the upper interval of the 95% confidence interval of the Standard Deviation.

See Also:

LogNormCDF

LogNormInvCDF

LogNormPDF

Probability Distributions