| Lognormal {base} | R Documentation |
Density, distribution function, quantile function and random
generation for the log normal distribution whose logarithm has mean
equal to meanlog and standard deviation equal to sdlog.
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)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations to generate. |
meanlog, sdlog |
mean and standard deviation of the distribution on the log scale. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
If meanlog or sdlog are not specified they assume the
default values of 0 and 1 respectively.
The log normal distribution has density
f(x) = 1/(sqrt(2 pi) sigma x) e^-((log x - mu)^2 / (2 sigma^2))
where μ and σ are the mean and standard deviation of the logarithm.
dlnorm gives the density,
plnorm gives the distribution function,
qlnorm gives the quantile function, and
rlnorm generates random deviates.
dnorm for the normal distribution.
dlnorm(1) == dnorm(0) x <- rlnorm(1000) # not yet always : all(abs(x - qlnorm(plnorm(x))) < 1e4 * .Machine$double.eps * x)