Log-normal distribution {dprop}

Compute the distributional properties of the log-normal distribution

Description

Compute the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the log-normal distribution.

Usage

d_lnormal(mu, sigma)

Arguments

mu

The location parameter (\mu\in\left(-\infty,+\infty\right)).

sigma

The strictly positive scale parameter of the log-normal distribution (\sigma > 0).

Details

The following is the probability density function of the log-normal distribution:

f(x)=\frac{1}{x\sigma\sqrt{2\pi}}e^{-\frac{\left(\log(x)-\mu\right)^{2}}{2\sigma^{2}}},

where x > 0, \mu\in\left(-\infty,+\infty\right) and \sigma > 0.

Value

d_lnormal gives the first four ordinary moments, central moments, mean, and variance, Pearson's coefficient of skewness and kurtosis, coefficient of variation, median and quartile deviation based on the selected parametric values of the log-normal distribution.

Author(s)

Muhammad Imran.

R implementation and documentation: Muhammad Imran [e-mail].

References

Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995). Continuous Univariate Distributions, Volume 1, Chapter 14. Wiley, New York.

See Also

d_normal

Examples

d_lnormal(1,0.5)