View source: R/mgplikelihoods.R
| clikmgp | R Documentation |
Censored likelihoods for 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.
clikmgp(
dat,
thresh,
mthresh = thresh,
loc,
scale,
shape,
par,
model = c("log", "neglog", "br", "xstud"),
likt = c("mgp", "pois", "binom"),
lambdau = 1,
...
)
dat |
matrix of observations |
thresh |
functional threshold for the maximum |
mthresh |
vector of individuals thresholds under which observations are censored |
loc |
vector of location parameter for the marginal generalized Pareto distribution |
scale |
vector of scale parameter for the marginal generalized Pareto distribution |
shape |
vector of shape parameter for the marginal generalized Pareto distribution |
par |
list of parameters: |
model |
string indicating the model family, one of |
likt |
string indicating the type of likelihood, with an additional contribution for the non-exceeding components: one of |
lambdau |
vector of marginal rate of marginal threshold exceedance. |
... |
additional arguments (see Details) |
Optional arguments can be passed to the function via ...
censored matrix of booleans and NA indicating whether observations dat fall below the mthreshold mthresh
cl cluster instance created by makeCluster (default to NULL)
ncors number of cores for parallel computing of the likelihood
numAbovePerRow number of observations above mthreshold (non-missing) per row
numAbovePerCol number of observations above mthreshold (non-missing) per column
mmax maximum per column
B1 number of replicates for quasi Monte Carlo integral for the exponent measure
B2 number of replicates for quasi Monte Carlo integral for the censored intensity contribution
genvec1 generating vector for the quasi Monte Carlo routine (exponent measure), associated with B1
genvec2 generating vector for the quasi Monte Carlo routine (individual obs contrib), associated with B2
the value of the log-likelihood with attributes expme, giving the exponent measure
The location and scale parameters are not identifiable unless one of them is fixed.
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