Lognormalb {mc2d} | R Documentation |
Density, distribution function, quantile function and random generation for a log normal distribution whose arithmetic mean equals to mean and standard deviation equals to sd.
dlnormb(x, mean = exp(0.5), sd = sqrt(exp(2) - exp(1)), log = FALSE) plnormb( q, mean = exp(0.5), sd = sqrt(exp(2) - exp(1)), lower.tail = TRUE, log.p = FALSE ) qlnormb( p, mean = exp(0.5), sd = sqrt(exp(2) - exp(1)), lower.tail = TRUE, log.p = FALSE ) rlnormb(n, mean = exp(0.5), sd = sqrt(exp(2) - exp(1)))
x, q |
vector of quantiles. |
mean |
the mean of the distribution. |
sd |
the standard deviation of the distribution. |
log, log.p |
logical. if 'TRUE' probabilities 'p' are given as 'log(p)'. |
lower.tail |
logical. if 'TRUE', probabilities are P[X ≤ x], otherwise, P[X > x]. |
p |
vector of probabilities. |
n |
number of observations. If 'length(n) > 1', the length is taken to be the number required. |
This function calls the corresponding density, distribution function, quantile function and random generation
from the log normal (see Lognormal
) after evaluation of meanlog = log(mean^2 / sqrt(sd^2+mean^2)) and
sqrt{(log(1+sd^2/mean^2))}
dlnormb gives the density, plnormb gives the distribution function, qlnormb gives the quantile function, and rlnormb generates random deviates. The length of the result is determined by n for rlnorm, and is the maximum of the lengths of the numerical arguments for the other functions. The numerical arguments other than n are recycled to the length of the result. Only the first elements of the logical arguments are used.
The default mean and sd are chosen to provide a distribution close to a lognormal with meanlog = 0 and sdlog = 1.
x <- rlnormb(1E5,3,6) mean(x) sd(x) dlnormb(1) == dnorm(0) dlnormb(1) == dlnorm(1)