Statistical analysis of a spatio-temporal model with
location dependent parameters and a test for spatial stationarity
In this paper we define a spatio-temporal model with location
dependent parameters to describe temporal variation and spatial
nonstationarity. We consider the prediction of observations at unknown
locations using known neighbouring observations. Further we propose
a local least squares based method to estimate the parameters at
The sampling properties of these estimators are investigated.
We also develop a statistical test for spatial
stationarity. In order to derive the asymptotic results we show that
the spatially nonstationary process can be locally approximated
by a spatially stationary process.
We illustrate the methods of estimation with some simulations and
a real data example.