llogis: Loglogistic Distribution

In Distributacalcul: Probability Distribution Functions

Description

Loglogistic distribution with shape parameter tau and scale parameter lambda.

Usage

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)

Arguments

x	vector of quantiles.
shape	shape parameter tau, must be positive
rate	rate parameter beta, must be positive.
scale	alternative parameterization to the rate parameter, scale = 1 / rate.
q	vector of quantiles.
lower.tail	logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x].
k	kth-moment.
d	cut-off value.
less.than.d	logical; if TRUE (default) truncated mean for values <= d, otherwise, for values > d.
kap	probability.

Details

The loglogistic distribution with shape parameter t and scale parameter lam has density:

f(x) = t lam^t x^(t - 1) / (lam^t + x^t)^2

for x > 0, lam, t > 0.

Value

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.

Examples

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)

Distributacalcul documentation built on Sept. 13, 2020, 5:19 p.m.