Abstract
This paper considers spatial regression problems for irregularly spaced data points. The choice of the parametric spatial model for the residuals and its influence on the testing of the regression coefficients is discussed in a maximum likelihood framework. An iterative estimation procedure based on estimated generalized least squares is also defined and some of its drawbacks are outlined. The various methods of analysis are compared in an example concerned with male lung cancer rates and industry in France.
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