Description Usage Arguments Value Note Author(s) References See Also Examples

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

1 2 3 | ```
rlnorm.rplus(n,meanlog,varlog)
dlnorm.rplus(x,meanlog,varlog)
``` |

`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 |

`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.

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).

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

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

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)
``` |

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