lscale.lgm: Update for latent Gaussian model for the scale parameter of a...

In lbelzile/mgp: Multivariate generalized Pareto models

Update for latent Gaussian model for the scale parameter of a generalized Pareto

Description

The scale has a log-Gaussian prior with variance lscale.tausq and precision (the inverse of the correlation matrix) given by lscale.precis.

Usage

lscale.lgm(scale, shape, ldat, lscale.mu, lscale.precis, lscale.tausq,
  mmax, discount = 1, maxstep = Inf)

Arguments

scale	vector of scale parameters for the generalized Pareto distribution
shape	vector of shape parameters for the generalized Pareto distribution
ldat	list with exceedances at each site
lscale.mu	mean of the log-Gaussian process for the scale
lscale.precis	precision matrix of the log-Gaussian process corresponding to the inverse of the correlation matrix
lscale.tausq	variance of the log-Gaussian process
mmax	vector of maximum of each series in ldat
discount	numeric giving the discount factor for the Newton Default to 1.
maxstep	maximum step size for the MCMC (proposal will be at most maxstep units away from the current value).

Value

a vector of scale parameters

lbelzile/mgp documentation built on Aug. 5, 2023, 2:34 a.m.