spatial.gev.bma: Run an MCMC to fit a hierarchical spatial generalized extreme...

In spatial.gev.bma: Hierarchical spatial generalized extreme value (GEV) modeling with Bayesian Model Averaging (BMA)

Description

This is the main function of the spatial.gev.bma package. It runs an MCMC to sample the posterior distribution of a spatial GEV model that takes a number of covariates for linear interactions as well as a spatial component to model dependent overdispersion.

Usage

spatial.gev.bma(Y.list, X.all, S, n.reps, prior.user = NULL,
full = FALSE, fixed.xi = NULL, print.every = 0)

Arguments

Y.list	This is a list of length n, where n is the total number of sites you have data for. Each element of the list is a vector of observations at that site.
X.all	This is an n by p matrix where n is the total number of sites and p is the total number of variables under consideration. Please supply your own constant in the first column. Note that this model implicitly assumes that at a given site, the covariates are constant throughout the observation period. Email me if you need something more flexible.
S	This is an n by 2 matrix with the coordinates of each of your n sites.
n.reps	The total number of repititions (i.e. includes burn in) that you would like to run the MCMC.
prior.user	A list containing any priors that the user would like to specify.
full	A boolean indicating if you'd like to force all variables to be included (TRUE) or whether you want to perform BMA (FALSE)
fixed.xi	If set to NULL, the shape parameter is estimated like the location and scale. If a numeric value is provided, the shape parameter is fixed at this level.
print.every	A simple tool to tell you how many iterations you've run. If you set it to 0 then no progress reports will be given. If it is a positive number, say x, then every x iterations it will tell you the total number of iterations.

Value

TAU	An n by reps by 3 array of the states of the random effects at each iteration
THETA	An reps by p by 3 array of the states of the linear terms at each iteration
ALPHA	A reps by 3 matrix of states of the alpha term at each iteration
LAMBDA	A reps by 3 matrix of states of the lambda term at each iteration

Author(s)

Alex Lenkoski <[e-mail]>

Examples

data(norway)
attach(norway)
##To replicate our results, change 2 to 2e5 below
a <- spatial.gev.bma(Y.list,X,S,2)  

spatial.gev.bma documentation built on May 1, 2019, 6:34 p.m.