ZeroModifiedLognormal: The Zero-Modified Lognormal (Delta) Distribution

Description

Density, distribution function, quantile function, and random generation for the zero-modified lognormal distribution with parameters meanlog, sdlog, and p.zero. The zero-modified lognormal (delta) distribution is the mixture of a lognormal distribution with a positive probability mass at 0.

Usage

dzmlnorm(x, meanlog = 0, sdlog = 1, p.zero = 0.5)
  pzmlnorm(q, meanlog = 0, sdlog = 1, p.zero = 0.5)
  qzmlnorm(p, meanlog = 0, sdlog = 1, p.zero = 0.5)
  rzmlnorm(n, meanlog = 0, sdlog = 1, p.zero = 0.5)

Arguments

vector of quantiles.

vector of probabilities between 0 and 1.

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

meanlog

vector of means of the normal (Gaussian) part of the distribution on the log scale. The default is meanlog=0.

sdlog

vector of (positive) standard deviations of the normal (Gaussian) part of the distribution on the log scale. The default is sdlog=1.

p.zero

vector of probabilities between 0 and 1 indicating the probability the random variable equals 0. For rzmlnorm this must be a single, non-missing number.

Value

dzmlnorm gives the density, pzmlnorm gives the distribution function, qzmlnorm gives the quantile function, and rzmlnorm generates random deviates.

Details

The zero-modified lognormal (delta) distribution is the mixture of a lognormal distribution with a positive probability mass at 0. This distribution was introduced without a name by Aitchison (1955), and the name $\Delta$-distribution was coined by Aitchison and Brown (1957, p.95). It is a special case of a zero-modified distribution (see Johnson et al., 1992, p. 312). Let $f(x; \mu, \sigma)$ denote the density of a lognormal random variable $X$ with parameters meanlog=$\mu$ and sdlog=$\sigma$. The density function of a zero-modified lognormal (delta) random variable $Y$ with parameters meanlog=$\mu$, sdlog=$\sigma$, and p.zero=$p$, denoted $h(y; \mu, \sigma, p)$, is given by: lll{ $h(y; \mu, \sigma, p) =$ $p$ for $y = 0$ $(1 - p) f(y; \mu, \sigma)$ for $y > 0$ } Note that $\mu$ is not the mean of the zero-modified lognormal distribution on the log scale; it is the mean of the lognormal part of the distribution on the log scale. Similarly, $\sigma$ is not the standard deviation of the zero-modified lognormal distribution on the log scale; it is the standard deviation of the lognormal part of the distribution on the log scale. Let $\gamma$ and $\delta$ denote the mean and standard deviation of the overall zero-modified lognormal distribution on the log scale. Aitchison (1955) shows that:

E [l o g (Y)] = γ = (1 - p) μ

V a r [l o g (Y)] = δ^{2} = (1 - p) σ^{2} + p (1 - p) μ^{2}

Note that when p.zero=$p$=0, the zero-modified lognormal distribution simplifies to the lognormal distribution.

References

Aitchison, J. (1955). On the Distribution of a Positive Random Variable Having a Discrete Probability Mass at the Origin. Journal of the American Statistical Association 50, 901-908. Aitchison, J., and J.A.C. Brown (1957). The Lognormal Distribution (with special reference to its uses in economics). Cambridge University Press, London. pp.94-99. Crow, E.L., and K. Shimizu. (1988). Lognormal Distributions: Theory and Applications. Marcel Dekker, New York, pp.47-51. Gibbons, RD., D.K. Bhaumik, and S. Aryal. (2009). Statistical Methods for Groundwater Monitoring. Second Edition. John Wiley and Sons, Hoboken, NJ. 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. Helsel, D.R. (2012). Statistics for Censored Environmental Data Using Minitab and R. Second Edition. John Wiley and Sons, Hoboken, NJ, Chapter 1. Johnson, N. L., S. Kotz, and A.W. Kemp. (1992). Univariate Discrete Distributions. Second Edition. John Wiley and Sons, New York, p.312. Owen, W., and T. DeRouen. (1980). Estimation of the Mean for Lognormal Data Containing Zeros and Left-Censored Values, with Applications to the Measurement of Worker Exposure to Air Contaminants. Biometrics 36, 707-719. USEPA (1992c). Statistical Analysis of Ground-Water Monitoring Data at RCRA Facilities: Addendum to Interim Final Guidance. Office of Solid Waste, Permits and State Programs Division, US Environmental Protection Agency, Washington, D.C. USEPA. (2009). Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities, Unified Guidance. EPA 530/R-09-007, March 2009. Office of Resource Conservation and Recovery Program Implementation and Information Division. U.S. Environmental Protection Agency, Washington, D.C.

Examples

Run this code

# Density of the zero-modified lognormal (delta) distribution with 
  # parameters meanlog=0, sdlog=1, and p.zero=0.5, evaluated at 
  # 0, 0.5, 1, 1.5, and 2:

  dzmlnorm(seq(0, 2, by = 0.5)) 
  #[1] 0.50000000 0.31374804 0.19947114 0.12248683 
  #[5] 0.07843701

  #----------

  # The cdf of the zero-modified lognormal (delta) distribution with 
  # parameters meanlog=1, sdlog=2, and p.zero=0.1, evaluated at 4:

  pzmlnorm(4, 1, 2, .1) 
  #[1] 0.6189203

  #----------

  # The median of the zero-modified lognormal (delta) distribution with 
  # parameters meanlog=2, sdlog=3, and p.zero=0.1:

  qzmlnorm(0.5, 2, 3, 0.1) 
  #[1] 4.859177

  #----------

  # Random sample of 3 observations from the zero-modified lognormal 
  # (delta) distribution with parameters meanlog=1, sdlog=2, and p.zero=0.4. 
  # (Note: The call to set.seed simply allows you to reproduce this example.)

  set.seed(20) 
  rzmlnorm(3, 1, 2, 0.4)
  #[1] 0.000000 0.000000 3.146641

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