LogMultinormalDistribution

LogMultinormalDistribution[μ,Σ]

represents a log-multinormal distribution with parameters μ and Σ.

Details

Background & Context

Examples

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Basic Examples  (4)

Probability density function:

Cumulative distribution function:

Mean and variance:

Covariance:

Scope  (6)

Generate a sample of pseudorandom vectors from a log-multinormal distribution:

Visualize the sample using a histogram:

Distribution parameters estimation:

Estimate the distribution parameters from sample data:

Goodness-of-fit test:

Skewness:

Limiting values:

Kurtosis:

Limiting values:

Hazard function:

Univariate marginals follow LogNormalDistribution:

Multivariate marginals follow a log-multinormal distribution:

Properties & Relations  (7)

Relationships to other distributions:

LogMultinormalDistribution is a transformation of MultinormalDistribution:

LogMultinormalDistribution is a transformation of BinormalDistribution:

One-dimensional marginal is LogNormalDistribution:

Special case with diagonal matrix is ProductDistribution of LogNormalDistribution:

LogMultinormalDistribution is related to LogNormalDistribution:

LogMultinormalDistribution is a slice distribution for GeometricBrownianMotionProcess:

Introduced in 2012
 (9.0)