# rlnorm: The multivariate lognormal distribution In compositions: Compositional Data Analysis

## Description

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

## Usage

 ```1 2 3``` ```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.

`rnorm.acomp`
 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```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) ```