seffEst: STFIT Spatial Effect Estimation

Description

STFIT Spatial Effect Estimation

Usage

seffEst(
  rmat,
  img.nrow,
  img.ncol,
  h.cov = 2,
  h.sigma2 = 2,
  weight.cov = NULL,
  weight.sigma2 = NULL,
  nnr,
  method = c("lc", "emp"),
  partial.only = TRUE,
  pve = 0.99,
  msk = NULL,
  msk.tol = 0.95,
  var.est = FALSE
)

Value

List of length 3 with entries:

seff_mat: estimated spatial effect matrix of the same shape as rmat.
seff_var_mat: estimated spatial effect variance matrix of the same shape as rmat.
idx: a list of two entries:
- idx.allmissing: index of the completely missing images.
- idx.imputed: index of the partially observed images, where spatial effects are estimated.

Arguments

rmat: residual matrix
img.nrow: image row dimension
img.ncol: image column dimension
h.cov: bandwidth for spatial covariance estimation; ignored if weight.cov is supplied
h.sigma2: bandwidth for sigma2 estimation
weight.cov: weight matrix for spatial covariance estimation
weight.sigma2: weight vector for spatial variance estimation
nnr: maximum number of nearest neighbor pixels to use for spatial covariance estimation
method: "lc" for local constant covariance estimation and "emp" for empirical covariance estimation
partial.only: calculate the spatical effect for partially observed images only, default is TRUE
pve: percent of variance explained of the selected eigen values. Default is 0.99.
msk: an optional logistic vector. TRUE represent the corresponding pixel is always missing.
msk.tol: if 'msk' is not given, the program will determine the mask using getMask function. If the percentage of missing values for a pixel over time is greater than this
var.est: Whether to estimate the variance of the temporal effect. Default is FALSE.