This paper is from Session 3F: Teaching nonparametric methods
which comes under Topic 3: Statistics education at the post-
secondary level Full topic list (Thursday 6th, 14:00-15:30)
Smoothing techniques in spatial statistics AbstractThe variogram
is one of the most important tools in the assessment of spatial
variability of a spatial statistical model. Estimation and
testing on this function is a crucial problem in random
processes inference, with several applications in a broad
spectrum of areas such as geostatistics, hydrology, atmospheric
sciences, etc. We show in this work how a generalized family of
variogram estimators can be built based on the classical ideas
of smoothing techniques in nonparametric regression. Some
examples will be given in order to compare the performance of
Nadaraya-Watson and Local Linear estimators with the empirical
variogram. The proper choice of the bandwidth for these methods
will be discussed. Some applications to atmospheric and/or
environmental data will also be provided. F