.BG
.FN Lognormal
.FN dlnorm
.FN plnorm
.FN qlnorm
.FN rlnorm
.TL
Lognormal Distribution
.CS
dlnorm(q, meanlog=0, sdlog=1)
plnorm(q, meanlog=0, sdlog=1)
qlnorm(p, meanlog=0, sdlog=1)
rlnorm(n, meanlog=0, sdlog=1)
.AG q
vector of (positive) quantiles.
Missing values (`NA's) are allowed.
.AG p
vector of probabilities.
Missing values (`NA's) are allowed.
.AG n
sample size.
If `length(n)' is larger than 1, then `length(n)' random values are returned.
.AG meanlog
.AG sdlog
vectors of means and standard deviations of the distribution
of the log of the random variable.  Thus, `exp(meanlog)' is a
scale parameter and `sdlog' is a shape parameter for the
lognormal distribution.
.RT
density (`dlnorm'),
probability (`plnorm'),
quantile (`qlnorm'), or
random sample (`rlnorm')
for the log-normal distribution with parameters `meanlog' and `sdlog'.
.SP
.Tr
The density function is given by
.sp
.EQ
delim $$
f sub m,s ( q ) ~=~
1 over { sqrt { 2 pi } s q } exp "{" - { 1 } over { 2 s sup 2 }
( log (q) ~-~ m ) sup 2 "}" ,
~~~ q ~>~ 0 , ~~ s ~>~ 0,
.EN
.sp
where $m$ and $s$ are the `meanlog' and `sdlog' parameters.
.En
.SE
The function `rlnorm' causes creation of the dataset `.Random.seed' if it does
not already exist, otherwise its value is updated.
.EX
log(rlnorm(50)) #hard way to generate a sample of normals
.KW distribution
.EQ
delim off
.EN
.WR
