EnvStats (version 2.4.0)

LognormalMix: Mixture of Two Lognormal Distributions

Description

Density, distribution function, quantile function, and random generation for a mixture of two lognormal distribution with parameters meanlog1, sdlog1, meanlog2, sdlog2, and p.mix.

Usage

dlnormMix(x, meanlog1 = 0, sdlog1 = 1, meanlog2 = 0, sdlog2 = 1, p.mix = 0.5)
  plnormMix(q, meanlog1 = 0, sdlog1 = 1, meanlog2 = 0, sdlog2 = 1, p.mix = 0.5) 
  qlnormMix(p, meanlog1 = 0, sdlog1 = 1, meanlog2 = 0, sdlog2 = 1, p.mix = 0.5) 
  rlnormMix(n, meanlog1 = 0, sdlog1 = 1, meanlog2 = 0, sdlog2 = 1, p.mix = 0.5)

Arguments

x

vector of quantiles.

q

vector of quantiles.

p

vector of probabilities between 0 and 1.

n

sample size. If length(n) is larger than 1, then length(n) random values are returned.

meanlog1

vector of means of the first lognormal random variable on the log scale. The default is meanlog1=0.

sdlog1

vector of standard deviations of the first lognormal random variable on the log scale. The default is sdlog1=1.

meanlog2

vector of means of the second lognormal random variable on the log scale. The default is meanlog2=0.

sdlog2

vector of standard deviations of the second lognormal random variable on the log scale. The default is sdlog2=1.

p.mix

vector of probabilities between 0 and 1 indicating the mixing proportion. For rlnormMix this must be a single, non-missing number.

Value

dlnormMix gives the density, plnormMix gives the distribution function, qlnormMix gives the quantile function, and rlnormMix generates random deviates.

Details

Let \(f(x; \mu, \sigma)\) denote the density of a lognormal random variable with parameters meanlog=\(\mu\) and sdlog=\(\sigma\). The density, \(g\), of a lognormal mixture random variable with parameters meanlog1=\(\mu_1\), sdlog1=\(\sigma_1\), meanlog2=\(\mu_2\), sdlog2=\(\sigma_2\), and p.mix=\(p\) is given by: $$g(x; \mu_1, \sigma_1, \mu_2, \sigma_2, p) = (1 - p) f(x; \mu_1, \sigma_1) + p f(x; \mu_2, \sigma_2)$$

References

Gilliom, R.J., and D.R. Helsel. (1986). Estimation of Distributional Parameters for Censored Trace Level Water Quality Data: 1. Estimation Techniques. Water Resources Research 22, 135-146.

Johnson, N. L., S. Kotz, and A.W. Kemp. (1992). Univariate Discrete Distributions. Second Edition. John Wiley and Sons, New York, pp.53-54, and Chapter 8.

Johnson, N. L., S. Kotz, and N. Balakrishnan. (1994). Continuous Univariate Distributions, Volume 1. Second Edition. John Wiley and Sons, New York.

See Also

Lognormal, NormalMix, Probability Distributions and Random Numbers.

Examples

# NOT RUN {
  # Density of a lognormal mixture with parameters meanlog1=0, sdlog1=1, 
  # meanlog2=2, sdlog2=3, p.mix=0.5, evaluated at 1.5: 

  dlnormMix(1.5, meanlog1 = 0, sdlog1 = 1, meanlog2 = 2, sdlog2 = 3, p.mix = 0.5) 
  #[1] 0.1609746

  #----------

  # The cdf of a lognormal mixture with parameters meanlog1=0, sdlog1=1, 
  # meanlog2=2, sdlog2=3, p.mix=0.2, evaluated at 4: 

  plnormMix(4, 0, 1, 2, 3, 0.2) 
  #[1] 0.8175281

  #----------

  # The median of a lognormal mixture with parameters meanlog1=0, sdlog1=1, 
  # meanlog2=2, sdlog2=3, p.mix=0.2: 

  qlnormMix(0.5, 0, 1, 2, 3, 0.2) 
  #[1] 1.156891

  #----------

  # Random sample of 3 observations from a lognormal mixture with 
  # parameters meanlog1=0, sdlog1=1, meanlog2=3, sdlog2=4, p.mix=0.2. 
  # (Note: the call to set.seed simply allows you to reproduce this example.)

  set.seed(20) 
  rlnormMix(3, 0, 1, 2, 3, 0.2) 
  #[1] 0.08975283 1.07591103 7.85482514
# }