a vector of length two or a matrix with two columns,
in which case the density/distribution is evaluated across
the rows.
n
number of observations.
dep
dependence parameter.
asy
a vector containing the two asymmetry parameters.
mar1, mar2
vectors of length three containing marginal
parameters.
log
logical; if TRUE, the log density is returned.
Value
dbvaneglog gives the density, pbvaneglog gives the
distribution function and rbvaneglog generates random deviates.
Details
The bivariate asymmetric negative logistic distribution function
with parameters parameters $\code{dep} = r$ and
$\code{asy} = (t_1,t_2)$ is
$$G(z_1,z_2) = \exp\left{-y_1-y_2+
[(t_1y_1)^{-r}+(t_2y_2)^{-r}]^{-1/r}\right}$$
where $r > 0$, $0 \leq t_1,t_2 \leq 1$, and
$$y_i = {1+s_i(z_i-a_i)/b_i}^{-1/s_i}$$
for $1+s_i(z_i-a_i)/b_i > 0$ and
$i = 1,2$, where the marginal
parameters are given by
$\code{mari} = (a_i,b_i,s_i)$,
$b_i > 0$.
If $s_i = 0$ then $y_i$ is defined by
continuity.
The univariate marginal distributions are generalized extreme
value.