gevr {mev} | R Documentation |
Generalized extreme value distribution (return level parametrization)
Description
Likelihood, score function and information matrix,
approximate ancillary statistics and sample space derivative
for the generalized extreme value distribution parametrized in terms of the return level z
, scale and shape.
Arguments
par |
vector of |
dat |
sample vector |
p |
tail probability, corresponding to |
method |
string indicating whether to use the expected ( |
nobs |
number of observations |
V |
vector calculated by |
Usage
gevr.ll(par, dat, p) gevr.ll.optim(par, dat, p) gevr.score(par, dat, p) gevr.infomat(par, dat, p, method = c('obs', 'exp'), nobs = length(dat)) gevr.Vfun(par, dat, p) gevr.phi(par, dat, p, V) gevr.dphi(par, dat, p, V)
Functions
-
gevr.ll
: log likelihood -
gevr.ll.optim
: negative log likelihood parametrized in terms of return levels,log(scale)
and shape in order to perform unconstrained optimization -
gevr.score
: score vector -
gevr.infomat
: observed information matrix -
gevr.Vfun
: vector implementing conditioning on approximate ancillary statistics for the TEM -
gevr.phi
: canonical parameter in the local exponential family approximation -
gevr.dphi
: derivative matrix of the canonical parameter in the local exponential family approximation
Author(s)
Leo Belzile