normal.params {bayescount} R Documentation

## Calculate the Normal Mean and Standard Deviation Using the Log-Normal Mean and Standard Deviation

### Description

Function to calculate the equivalent values for the mean and standard deviation of a normal distribution from the mean and standard deviation of the log-normal distribution. Outputs from this function can be used with the dnorm() function, and with the normal distribution in JAGS.

### Usage

`normal.params(log.mean, log.sd, coeff.variation=sqrt(exp(log.sd^2)-1))`

### Arguments

 `log.mean` either a single value or vector of values for the mean of the lognormal distribution. `log.sd` either a single value or vector of values for the standard deviation of the lognormal distribution. Ignored if values are supplied for coeff.variation. `coeff.variation` either a single value or vector of values for the coefficient of dispersion.

### Value

A list with elements representing the mean of the normal distribution, the standard deviation of the normal distribution, and the coefficient of variation.

### See Also

`lnormal.params`

### Examples

```
## Not run:
lmean <- 2.5
lsd <- 0.2
mean <- normal.params(lmean,lsd)[]
sd <- normal.params(lmean,lsd)[]

curve(dlnorm(x, lmean, lsd), from=0, to=25)
dev.new()
curve(dnorm(x, mean, sd), from=0, to=25)

## End(Not run)

```

[Package bayescount version 0.9.99-5 Index]