  We consider the smoothed version of sliced average variance estimation (SAVE)
dimension reduction method for dealing with spatially dependent data that are
observations of a strongly mixing random field. We propose kernel estimators
for the interest matrix and the effective dimension reduction (EDR) space, and
show their consistency.
