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

### Examples

```
lmean <- 2.5
lsd <- 0.2
mean <- normal.params(lmean,lsd)[[1]]
sd <- normal.params(lmean,lsd)[[2]]
curve(dlnorm(x, lmean, lsd), from=0, to=25, col="blue")
curve(dnorm(x, mean, sd), from=0, to=25, add=TRUE, col="red")
```

*bayescount*version 0.9.99-9 Index]