Mean of the underlying normal distribution
Standard deviation (σ > 0) of the underlying normal distribution
Mean of the underlying normal distribution
Standard deviation of the underlying normal distribution
Cumulative distribution function (CDF)
Value (x > 0)
Cumulative probability up to x
Mean of the distribution
E[X] = exp(μ + σ² / 2)
Probability density function (PDF)
Value (x > 0)
Probability density at x
Generate a random sample using inverse transform sampling.
Variance of the distribution
Var[X] = [exp(σ²) - 1] * exp(2μ + σ²)
Class representing the Log-Normal distribution. If X ~ LogNormal(μ, σ²), then ln(X) ~ Normal(μ, σ²).