bayescount (version 0.8.2)

normal.params: 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)

Value

Either a vector of length 2 representing the mean of the normal distribution as the first element and the standard deviation of the normal distribution as the second element, or a matrix with column 1 as the mean and column 2 as the standard deviation.

See Also

bayescount lnormal.params

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)
x11()
curve(dnorm(x, mean, sd), from=0, to=25)