We introduce methods for estimating the spectral density of a random field on a-dimensional
lattice from incomplete gridded data. Data are iteratively imputed onto an expanded lattice …

We provide a computationally and statistically efficient method for estimating the parameters
of a stochastic covariance model observed on a regular spatial grid in any number of …

The measurement of spatial dependence within a set of observations or the residuals from a
regression is one of the most common operations within spatial analysis. However, there …

Current statistics literature on statistical inference of random fields typically assumes that the
fields are stationary or focuses on models of non-stationary Gaussian fields with parametric …

Motivated by the need for analysing large spatio-temporal panel data, we introduce a novel
dimensionality reduction methodology for $ n $-dimensional random fields observed across …

This paper develops a frequency domain bootstrap method for random fields on Z 2. Three
frequency domain bootstrap schemes are proposed to bootstrap Fourier coefficients of …

In this paper, we study the asymptotic theory for spectral analysis of stationary random fields
on Z 2, including linear and nonlinear fields. Asymptotic properties of Fourier coefficients …

Generally speaking, the field of spatial statistics deals with the statistical inference of random
objects that are embedded into the Euclidean space Rd such as random closed sets …