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\name{Lognormal}\alias{dlnorm}\alias{plnorm}\alias{qlnorm}\alias{rlnorm}\title{The Log Normal Distribution}\description{Density, distribution function, quantile function and randomgeneration for the log normal distribution whose logarithm has meanequal to \code{meanlog} and standard deviation equal to \code{sdlog}.}\usage{dlnorm(x, meanlog = 0, sdlog = 1, log = FALSE)plnorm(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)qlnorm(p, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)rlnorm(n, meanlog = 0, sdlog = 1)}\arguments{\item{x, q}{vector of quantiles.}\item{p}{vector of probabilities.}\item{n}{number of observations to generate.}\item{meanlog, sdlog}{mean and standard deviation of the distributionon the log scale.}\item{log, log.p}{logical; if TRUE, probabilities p are given as log(p).}\item{lower.tail}{logical; if TRUE (default), probabilities are\eqn{P[X \le x]}{P[X <= x]}, otherwise, \eqn{P[X > x]}{P[X > x]}.}}\value{\code{dlnorm} gives the density,\code{plnorm} gives the distribution function,\code{qlnorm} gives the quantile function, and\code{rlnorm} generates random deviates.}\details{If \code{meanlog} or \code{sdlog} are not specified they assume thedefault values of \code{0} and \code{1} respectively.The log normal distribution has density\deqn{f(x) = \frac{1}{\sqrt{2\pi}\sigma x} e^{-(\log(x) - \mu)^2/2 \sigma^2}%}{f(x) = 1/(sqrt(2 pi) sigma x) e^-((log x - mu)^2 / (2 sigma^2))}where \eqn{\mu} and \eqn{\sigma} are the mean and standarddeviation of the logarithm.}\note{The cumulative hazard \eqn{H(t) = - \log(1 - F(t))}{H(t) = - log(1 - F(t))}is \code{-plnorm(t, r, lower = FALSE, log = TRUE)}.}\seealso{\code{\link{dnorm}} for the normal distribution.}\examples{dlnorm(1) == dnorm(0)x <- rlnorm(1000) # not yet always :all(abs(x - qlnorm(plnorm(x))) < 1e4 * .Machine$double.eps * x)}\keyword{distribution}