| 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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