# mlorm

From bda v14.1.4
by Bin Wang

##### The mixed lognormal distribution

Density, distribution function, quantile function and random generation for the lognormal mixture distribution with means equal to 'mu' and standard deviations equal to 's'.

- Keywords
- distribution

##### Usage

```
dmlnorm(x,p,mean,sd)
pmlnorm(q,p,mean,sd)
qmlnorm(prob,p,mean,sd)
rmlnorm(n,p,mean,sd)
```

##### Arguments

- x,q
vector of quantiles in dmixnorm and pmixnorm. In qmixnorm, 'x' is a vector of probabilities.

- p
proportions of the mixture components.

- prob
A vector of probabilities.

- n
number of observations. If 'length(n) > 1', the length is taken to be the number required.

- mean
vector of means

- sd
vector of standard deviations

##### Value

return the density, probability, quantile and random value for the four functions, respectively.

##### Examples

```
# NOT RUN {
p <- c(.4,.6)
mu <- c(1,4)
s <- c(2,3)
dmlnorm(c(0,1,2,20),p,mu,s)
pmlnorm(c(0,1,2,20),p,mu,s)
qmlnorm(c(0,1,.2,.20),p,mu,s)
rmlnorm(3,p,mu,s)
# }
```

*Documentation reproduced from package bda, version 14.1.4, License: Unlimited*

### Community examples

Looks like there are no examples yet.