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The problem of estimating the intensity of a non-stationary Poisson point process arises in many applications. Besides non parametric solutions, e. g. kernel estimators, parametric methods based on maximum likelihood estimation are of interest. In the present paper we have developed an approach in which the parametric function is represented by two-dimensional beta-splines.
This paper describes a modification of the kriging method for working with the square root transformation of a spatial random process. We have developed this method for the situation where the spatial process observed is not supposed to be stationary but the assumption is that its square root is a second order stationary spatial random process. Consequently this method is developed for estimating the integral of the process observed and finally some application of the method is given to data from...
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