Spatial representation of economic and financial measures used in agriculture via wavelet analysis

A foundation is set forth for use of the wavelet transform as a spatial ana lysis tool for modelling the geographical representation of economic and fi nancial measures used in agriculture. This provides a framework from which to estimate a smooth nonparametric function which describes complex, multiv ariate relationships embedded in spatial data, with the resulting maps conv eying large amounts of information in a familiar format. We illustrate this approach for tasks which include the graphical presentation of information , density estimation and wavelet-based nonparametric regression. A redundan t wavelet transform is used, and we detail the properties which make it par ticularly appropriate for these objectives.