Mean and SD of lognormal attribute correlated with another attribute
Posted: 17 Jan 2022, 10:07
Hi all,
If I have two attributes of time: lognormally distributed and correlated as following:
time1 <- -exp(m1 + s1 * draws1)
time2 <- -exp(m2 + s2 * draws2 + s1_2 * draws1)
Now if I want to find the mean and sd for the random variable time2,
is this the correct way of doing that?
Find the unconditionals from the model and find mean and sd as following:
mean = mean(as.vector(unconditionals$time2))
sd = sd(as.vector(unconditionals$time2))
Is this the correct way of finding mean and sd? (Or for narrower distribution using conditionals instead of unconditional)
If I have two attributes of time: lognormally distributed and correlated as following:
time1 <- -exp(m1 + s1 * draws1)
time2 <- -exp(m2 + s2 * draws2 + s1_2 * draws1)
Now if I want to find the mean and sd for the random variable time2,
is this the correct way of doing that?
Find the unconditionals from the model and find mean and sd as following:
mean = mean(as.vector(unconditionals$time2))
sd = sd(as.vector(unconditionals$time2))
Is this the correct way of finding mean and sd? (Or for narrower distribution using conditionals instead of unconditional)