Likelihood for the various parametric limiting models over region determined by
$$\{y \in F: \max_{j=1}^D \sigma_j \frac{y^\xi_j-1}{\xi_j}+\mu_j > u\};$$
where \(\mu\) is loc
, \(\sigma\) is scale
and \(\xi\) is shape
.
likmgp(
dat,
thresh,
loc,
scale,
shape,
par,
model = c("log", "br", "xstud"),
likt = c("mgp", "pois", "binom"),
lambdau = 1,
...
)
the value of the log-likelihood with attributes
expme
, giving the exponent measure
matrix of observations
functional threshold for the maximum
vector of location parameter for the marginal generalized Pareto distribution
vector of scale parameter for the marginal generalized Pareto distribution
vector of shape parameter for the marginal generalized Pareto distribution
list of parameters: alpha
for the logistic model, Lambda
for the Brown--Resnick model or else Sigma
and df
for the extremal Student.
string indicating the model family, one of "log"
, "neglog"
, "br"
or "xstud"
string indicating the type of likelihood, with an additional contribution for the non-exceeding components: one of "mgp"
, "binom"
and "pois"
.
vector of marginal rate of marginal threshold exceedance.
additional arguments (see Details)
Optional arguments can be passed to the function via ...
cl
cluster instance created by makeCluster
(default to NULL
)
ncors
number of cores for parallel computing of the likelihood
mmax
maximum per column
B1
number of replicates for quasi Monte Carlo integral for the exponent measure
genvec1
generating vector for the quasi Monte Carlo routine (exponent measure), associated with B1