| ccbvevd {evd} | R Documentation |
Conditional copula functions, conditioning on either margin, for nine parametric bivariate extreme value models.
ccbvevd(x, mar = 2, dep, asy = c(1, 1), alpha, beta, model = "log",
lower.tail = TRUE)
x |
A matrix or data frame, ordinarily with two columns,
which may contain missing values. A data frame may also
contain a third column of mode logical, which
itself may contain missing values (see Details). |
mar |
One or two; conditions on this margin. |
dep |
Dependence parameter for the logistic, asymmetric logistic, Husler-Reiss, negative logistic and asymmetric negative logistic models. |
asy |
A vector of length two, containing the two asymmetry parameters for the asymmetric logistic and asymmetric negative logistic models. |
alpha, beta |
Alpha and beta parameters for the bilogistic, negative bilogistic, Coles-Tawn and asymmetric mixed models. |
model |
The specified model; a character string. Must be
either "log" (the default), "alog", "hr",
"neglog", "aneglog", "bilog",
"negbilog", "ct" or "amix" (or any unique
partial match), for the logistic, asymmetric logistic,
Husler-Reiss, negative logistic, asymmetric negative logistic,
bilogistic, negative bilogistic, Coles-Tawn and asymmetric
mixed models respectively. If parameter arguments are given
that do not correspond to the specified model those arguments
are ignored, with a warning. |
lower.tail |
Logical; if TRUE (default), the
conditional distribution function is returned; the conditional
survivor function is returned otherwise. |
The function calculates P(U1 < x1|U2 = x2), where
(U1,U2) is a random vector with Uniform(0,1) margins
and with a dependence structure given by the specified
parametric model. By default, the values of x1 and
x2 are given by the first and second columns of the
argument x. If mar = 1 then this is reversed.
If x has a third column x3 of mode logical, then
the function returns P(U1 < x1|U2 = x2,I = x3), according
to inference proceedures derived by Stephenson and Tawn (2004).
See fbvevd. This requires numerical integration,
and hence will be slower.
This function is mainly for internal use. It is used by
plot.bvevd to calculate the conditional P-P
plotting diagnostics.
A numeric vector of probabilities.
Stephenson, A. G. and Tawn, J. A. (2004) Exploiting Occurence Times in Likelihood Inference for Componentwise Maxima. Biometrika 92(1), 213–217.