calculate_posterior_VL {GPvecchia}

Vecchia Laplace extension of GPVecchia for non-Gaussian data

Description

Vecchia Laplace extension of GPVecchia for non-Gaussian data

Usage

calculate_posterior_VL(
  z,
  vecchia.approx,
  likelihood_model = c("gaussian", "logistic", "poisson", "gamma", "beta", "gamma_alt"),
  covparms,
  covmodel = "matern",
  likparms = list(alpha = 2, sigma = sqrt(0.1)),
  max.iter = 50,
  convg = 1e-06,
  return_all = FALSE,
  y_init = NA,
  prior_mean = rep(0, length(z)),
  verbose = FALSE
)

Arguments

z

an array of real numbers representing observations

vecchia.approx

a vecchia object as generated by vecchia_specify()

likelihood_model

text describing likelihood model to be used for observations. Can be "gaussian","logistic", "poisson", "gamma", or "beta"

covparms

covariance parameters as a vector

covmodel

type of the model covariance or selected elements of the covariance matrix

likparms

likelihood parameters for the likelihood_model, as a list. Default values are sqrt(.1) for Gaussian noise and 2 for the alpha parameter for Gamma data.

max.iter

maximum iterations to perform

convg

convergence criteria. End iterations if the Newton step is this small

return_all

Return additional posterior covariance terms, TRUE or FALSE

y_init

Specify initial guess for posterior mode

prior_mean

specify the prior latent mean

verbose

if TRUE messages about the posterior estimation will be displayed

Value

multivariate normal posterior parameters calculated by the Vecchia-Laplace approximation

Examples

z=rnorm(10); locs=matrix(1:10,ncol=1); vecchia.approx=vecchia_specify(locs,m=5)
calculate_posterior_VL(z,vecchia.approx,"gaussian",covparms=c(1,2,.5))