llogis | R Documentation |
Loglogistic distribution with shape parameter \tau
and scale
parameter \lambda
.
dLlogis(x, shape, rate = 1/scale, scale = 1/rate)
pLlogis(q, shape, rate = 1/scale, scale = 1/rate, lower.tail = TRUE)
expValLlogis(shape, rate = 1/scale, scale = 1/rate)
varLlogis(shape, rate = 1/scale, scale = 1/rate)
kthMomentLlogis(k, shape, rate = 1/scale, scale = 1/rate)
expValLimLlogis(d, shape, rate = 1/scale, scale = 1/rate)
expValTruncLlogis(d, shape, rate = 1/scale, scale = 1/rate, less.than.d = TRUE)
stopLossLlogis(d, shape, rate = 1/scale, scale = 1/rate)
meanExcessLlogis(d, shape, rate = 1/scale, scale = 1/rate)
VatRLlogis(kap, shape, rate = 1/scale, scale = 1/rate)
TVatRLlogis(kap, shape, rate = 1/scale, scale = 1/rate)
x , q |
vector of quantiles. |
shape |
shape parameter |
rate |
rate parameter |
scale |
alternative parameterization to the rate parameter, scale = 1 / rate. |
lower.tail |
logical; if TRUE (default), probabilities are
|
k |
kth-moment. |
d |
cut-off value. |
less.than.d |
logical; if |
kap |
probability. |
The loglogistic distribution with shape parameter \tau
and scale parameter
\lambda
has density:
\frac{\tau \lambda^\tau x^{\tau -1}}{(\lambda^{\tau }+x^{\tau })^{2}}
for x \in \mathcal{R}^+
, \lambda, \tau > 0
.
Function :
dLlogis
gives the probability density function (PDF).
pLlogis
gives the cumulative density function (CDF).
expValLlogis
gives the expected value.
varLlogis
gives the variance.
kthMomentLlogis
gives the kth moment.
expValLimLlogis
gives the limited mean.
expValTruncLlogis
gives the truncated mean.
stopLossLlogis
gives the stop-loss.
meanExcessLlogis
gives the mean excess loss.
VatRLlogis
gives the Value-at-Risk.
TVatRLlogis
gives the Tail Value-at-Risk.
Invalid parameter values will return an error detailing which parameter is problematic.
dLlogis(x = 2, shape = 2, scale = 4)
# With scale parameter
pLlogis(q = 3, shape = 3, scale = 5)
# With rate parameter
pLlogis(q = 3, shape = 3, rate = 0.2)
# Survival function
pLlogis(q = 3, shape = 3, rate = 0.2, lower.tail = FALSE)
expValLlogis(shape = 2, scale = 4)
varLlogis(shape = 3, scale = 4)
kthMomentLlogis(k = 3, shape = 5, scale = 4)
expValLimLlogis(d = 2, shape = 2, scale = 4)
# With rate parameter
expValTruncLlogis(d = 2, shape = 2, scale = 4)
# Values greater than d
expValTruncLlogis(d = 2, shape = 2, scale = 4, less.than.d = FALSE)
stopLossLlogis(d = 2, shape = 2, scale = 4)
meanExcessLlogis(d = 3, shape = 2, scale = 4)
# With scale parameter
VatRLlogis(kap = .2, shape = 2, scale = 4)
# With rate parameter
VatRLlogis(kap = .2, shape = 2, rate = 0.25)
# With scale parameter
TVatRLlogis(kap = .2, shape = 3, scale = 4)
# With rate parameter
TVatRLlogis(kap = .2, shape = 3, rate = 0.25)
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