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)

Arguments

log.mean either a single value or vector of values for the mean of the log-normal distribution
log.sd either a single value or vector of values for the standard deviation of the log-normal distribution

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.

Author(s)

Matthew Denwood m.denwood@vet.gla.ac.uk funded as part of the DEFRA VTRI project 0101.

See Also

bayescount lnormal.params

Examples


## Not run: 
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)
## End(Not run)


[Package bayescount version 0.8.2 Index]