ZINB_GP_count — ZINB_GP_count • ZINB.GP

Run the ZINB GP model with GP random effects only in the count part.

Usage

ZINB_GP_count(
  X,
  y,
  coords,
  Vs,
  Vt,
  Ds,
  Dt,
  nsim,
  burn,
  thin = 1,
  save_ypred = FALSE,
  print_iter = 100,
  print_progress = FALSE,
  ltPrior = NULL,
  lsPrior = NULL,
  sigmaPrior = NULL,
  noisePrior = NULL,
  mh_sd_r = NULL,
  kern = NULL
)

Arguments

X: Fixed-effect design matrix with one row per observation.
y: Non-negative integer count response.
coords: Spatial coordinate matrix with one row per full spatial level, including the baseline level omitted from Vs.
Vs: Spatial random-effect design matrix with one row per observation.
Vt: Temporal random-effect design matrix with one row per observation.
Ds: Spatial distance matrix; its diagonal must be zero.
Dt: Temporal distance matrix; its diagonal must be zero.
nsim: Total number of MCMC iterations; must exceed burn.
burn: Number of burn-in iterations.
thin: Store every thin-th iteration after burn-in.
save_ypred: Whether to save posterior predictive draws.
print_iter: Print progress every print_iter iterations.
print_progress: Whether to print MCMC progress.
ltPrior: List with max, mh_sd, a, and b for temporal length-scale prior and proposal controls.
lsPrior: List with max, mh_sd, a, and b for spatial length-scale prior and proposal controls.
sigmaPrior: List with a and b inverse-gamma prior parameters for GP scales.
noisePrior: List with a, b, and mh_sd for the GP noise-ratio prior and proposal.
mh_sd_r: Proposal standard deviation for the negative-binomial dispersion parameter.
kern: Kernel function accepting a distance matrix and length scale.

Value

A list containing posterior MCMC draws for the count GP, fixed effects, and the negative-binomial dispersion parameter.