X is distributed as a lognormal if its log is Normally distributed, or (equivalently) it is the exp of a normally distributed random variable.
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Parameters |
Mean \(mu\), Variance \(\sigma ^{2}\). The mean has to be positive. It can also be parameterized with the mean and variance of the underlying normal. |
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Support |
\(\left( 0 ,\infty \right) \) |
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Main Uses |
Models for data that are constrained to be positive, are generally small (close to zero) with a few large values. |
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Random Draws |
%RANLOGNORMAL(mean,sd) draws one or more random log Normals with the given mean and standard deviation. |
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Moment Matching |
%LOGNORMALPARMS(mean,sd) (external function) returns the 2-VECTOR of the mean and standard deviation required for the underlying Normal whose exp will give a lognormal with the required mean and standard deviation. |
Copyright © 2026 Thomas A. Doan