rlnorm {compositions}

The multivariate lognormal distribution

Description

Generates random amounts with a multivariate lognormal distribution, or gives the density of that distribution at a given point.

Usage

rlnorm.rplus(n,meanlog,varlog)
dlnorm.rplus(x,meanlog,varlog)
          

Arguments

n

number of datasets to be simulated

meanlog

the mean-vector of the logs

varlog

the variance/covariance matrix of the logs

x

vectors in the sample space

Value

rlnorm.rplus gives a generated random dataset of class "rplus" following a lognormal distribution with logs having mean meanlog and variance varlog.
dlnorm.rplus gives the density of the distribution with respect to the Lesbesgue measure on R+ as a subset of R.

Note

The main difference between rlnorm.rplus and rnorm.aplus is that rlnorm.rplus needs a logged mean. The additional difference for the calculation of the density by dlnorm.rplus and dnorm.aplus is the reference measure (a log-Lebesgue one in the second case).

Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de, Raimon Tolosana-Delgado

References

Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman & Hall Ltd., London (UK). 416p.

See Also

rnorm.acomp

Examples

MyVar <- matrix(c(
0.2,0.1,0.0,
0.1,0.2,0.0,
0.0,0.0,0.2),byrow=TRUE,nrow=3)
MyMean <- c(1,1,2)

plot(rlnorm.rplus(100,log(MyMean),MyVar))
plot(rnorm.aplus(100,MyMean,MyVar))
x <- rnorm.aplus(5,MyMean,MyVar)
dnorm.aplus(x,MyMean,MyVar)
dlnorm.rplus(x,log(MyMean),MyVar)