gevr {mev} | R Documentation |
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.
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 |
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)
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
Leo Belzile