Vector implementing conditioning on approximate ancillary statistics for the TEM
Canonical parameter in the local exponential family approximation
gpde.Vfun(par, dat, m)gpde.phi(par, dat, V, m)
gpde.dphi(par, dat, V, m)
vector of length 2 containing \(e_m\) and \(\xi\), respectively the expected shortfall at probability 1/(1-\(\alpha\)) and the shape parameter.
sample vector
number of observations of interest for return levels. See Details
vector calculated by gpde.Vfun