Description Usage Arguments Details Value Note Examples
Inverse Gaussian distribution with mean mu and shape parameter beta.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | expValIG(mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
varIG(mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
expValLimIG(d, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
expValTruncIG(
d,
mean,
shape = dispersion * mean^2,
dispersion = shape/mean^2,
less.than.d = TRUE
)
stopLossIG(d, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
meanExcessIG(d, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
VatRIG(kap, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
TVatRIG(kap, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
mgfIG(t, mean, shape = dispersion * mean^2, dispersion = shape/mean^2)
|
mean |
mean (location) parameter mu, must be positive. |
shape |
shape parameter beta, must be positive |
dispersion |
alternative parameterization to the shape parameter, dispersion = 1 / rate. |
d |
cut-off value. |
less.than.d |
logical; if |
kap |
probability. |
t |
t. |
The Inverse Gaussian distribution with
Function :
expValIG
gives the expected value.
varIG
gives the variance.
expValLimIG
gives the limited mean.
expValTruncIG
gives the truncated mean.
stopLossIG
gives the stop-loss.
meanExcessIG
gives the mean excess loss.
VatRIG
gives the Value-at-Risk.
TVatRIG
gives the Tail Value-at-Risk.
mgfIG
gives the moment generating function (MGF).
Invalid parameter values will return an error detailing which parameter is problematic.
Function VatRIG is a wrapper for the qinvgauss
function from the statmod package.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | expValIG(mean = 2, shape = 5)
varIG(mean = 2, shape = 5)
expValLimIG(d = 2, mean = 2, shape = 5)
expValTruncIG(d = 2, mean = 2, shape = 5)
stopLossIG(d = 2, mean = 2, shape = 5)
meanExcessIG(d = 2, mean = 2, shape = 5)
VatRIG(kap = 0.99, mean = 2, shape = 5)
TVatRIG(kap = 0.99, mean = 2, shape = 5)
mgfIG(t = 1, mean = 2, shape = .5)
|
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