Description Usage Arguments Details Value Note Examples
Lognormal distribution with mean mu and variance sigma.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | expValLnorm(meanlog, sdlog)
varLnorm(meanlog, sdlog)
kthMomentLnorm(k, meanlog, sdlog)
expValLimLnorm(d, meanlog, sdlog)
expValTruncLnorm(d, meanlog, sdlog, less.than.d = TRUE)
stopLossLnorm(d, meanlog, sdlog)
meanExcessLnorm(d, meanlog, sdlog)
VatRLnorm(kap, meanlog, sdlog)
TVatRLnorm(kap, meanlog, sdlog)
|
meanlog |
location parameter mu. |
sdlog |
standard deviation sigma, must be positive. |
k |
kth-moment. |
d |
cut-off value. |
less.than.d |
logical; if |
kap |
probability. |
The Log-normal distribution with mean mu and standard deviation sigma has density:
f(x) = e^(-(1/2) ((ln(x) - mu)/sigma)^2) / ((2 pi)^(1/2) sigma x
for x >= 0, mu real, sigma > 0.
Function :
expValLnorm
gives the expected value.
varLnorm
gives the variance.
kthMomentLnorm
gives the kth moment.
expValLimLnorm
gives the limited mean.
expValTruncLnorm
gives the truncated mean.
stopLossLnorm
gives the stop-loss.
meanExcessLnorm
gives the mean excess loss.
VatRLnorm
gives the Value-at-Risk.
TVatRLnorm
gives the Tail Value-at-Risk.
Invalid parameter values will return an error detailing which parameter is problematic.
Function VatRLnorm is a wrapper of the qlnorm
function from the stats package.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | expValLnorm(meanlog = 3, sdlog = 5)
varLnorm(meanlog = 3, sdlog = 5)
kthMomentLnorm(k = 2, meanlog = 3, sdlog = 5)
expValLimLnorm(d = 2, meanlog = 2, sdlog = 5)
expValTruncLnorm(d = 2, meanlog = 2, sdlog = 5)
# Values greater than d
expValTruncLnorm(d = 2, meanlog = 2, sdlog = 5, less.than.d = FALSE)
stopLossLnorm(d = 2, meanlog = 2, sdlog = 5)
meanExcessLnorm(d = 2, meanlog = 2, sdlog = 5)
VatRLnorm(kap = 0.8, meanlog = 3, sdlog = 5)
TVatRLnorm(kap = 0.8, meanlog = 2, sdlog = 5)
|
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