| Lnorm | R Documentation |
Lognormal distribution with mean \mu and variance \sigma.
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 |
sdlog |
standard deviation |
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:
\frac{1}{\sqrt{2\pi}\sigma x}\textrm{e}^{-\frac{1}{2}\left(\frac{\ln(x) - \mu}{\sigma}\right)^2}
for x \in \mathcal{R}^{+}, \mu \in \mathcal{R}, \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.
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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