mev (version 1.17)

pp.infomat: Information matrix for the Poisson process likelihood

Description

The function returns the expected or observed information matrix.

Usage

pp.infomat(par, dat, method = c("obs", "exp"), u, np = 1, nobs = length(dat))

Value

information matrix of the NHPP

Arguments

par

vector of loc, scale and shape

dat

sample vector

method

string indicating whether to use the expected ('exp') or the observed ('obs' - the default) information matrix.

u

threshold

np

number of periods of observations. This is a post hoc adjustment for the intensity so that the parameters of the model coincide with those of a generalized extreme value distribution with block size length(dat)/np.

nobs

number of observations for the expected information matrix. Default to length(dat) if dat is provided.

References

Sharkey, P. and J.A. Tawn (2017). A Poisson process reparameterisation for Bayesian inference for extremes, Extremes, 20(2), 239-263, http://dx.doi.org/10.1007/s10687-016-0280-2.

See Also

pp

Examples

if (FALSE) {
dat <- rgp(n <- 1e3, 0.1, 2, -0.1)
np <- 10
mle <- fit.pp(dat, threshold = 0, np =  np)$par
info_obs <- pp.infomat(par = mle, dat = dat, method = "obs", u = 0, np = np)
info_exp <- pp.infomat(par = mle, dat = dat, method = "exp", u = 0, np = np)
info_obs/info_exp
}