Bratt Swan - 9 months ago 40

R Question

Below is my code:

`set.seed(1)`

par(mfrow=c(1,2))

lognorm.gen <- function(mu,sigma){

ns <- rnorm(1000,mu,sigma)

ns <- exp(ns)

hist(ns,probability = T, main = expression(paste("Sample Density Curve", mu, sigma)))

y <- seq(0,15,length=100)

lines(y,dlnorm(y,mu,sigma))

}

lognorm.gen(0,0.25)

I generated samples from normal then transformed them into lognormal distribution. Firstly, I am using

`mu`

`sigma`

`rnorm()`

`exp(mu)`

`exp(sigma)`

`dlnorm()`

`mu`

`sigma`

`dlnorm()`

`exp(mu)`

Answer

Please read `?dlnorm`

:

```
dlnorm(x, meanlog = 0, sdlog = 1, log = FALSE)
plnorm(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
qlnorm(p, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
rlnorm(n, meanlog = 0, sdlog = 1)
meanlog, sdlog: mean and standard deviation of the distribution on the
log scale with default values of ‘0’ and ‘1’ respectively.
```

Mean and standard deviation are specified in **log scale**. That is why you still need the same `mu`

and `sigma`

as you used in `rnorm`

, not `exp(mu)`

and `exp(sigma)`

.

Source (Stackoverflow)