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Inverse Distance Weighting as a sum of all weighting functions for each sample point. Each function has the value of one of the samples at its sample point and zero at every other sample point. Inverse distance weighting ( IDW ) is a type of deterministic method for multivariate interpolation with a known scattered set of points.
Natural neighbor interpolation with Laplace weights. The interface l(x i) between the cells linked to x and x i is in blue, while the distance d(x i) between x and x i is in red. Laplace weights [2] [3]
The theoretical basis for the method was developed by the French mathematician Georges Matheron in 1960, based on the master's thesis of Danie G. Krige, the pioneering plotter of distance-weighted average gold grades at the Witwatersrand reef complex in South Africa. Krige sought to estimate the most likely distribution of gold based on samples ...
One very early weighted estimator is the Horvitz–Thompson estimator of the mean. [3] When the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used to weight the observations. This approach has been generalized to many aspects of statistics under ...
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In a multiplicatively weighted Voronoi diagram, the distance between a point and a site is divided by the (positive) weight of the site. [1] In the plane under the ordinary Euclidean distance , the multiplicatively weighted Voronoi diagram is also called circular Dirichlet tessellation [ 2 ] [ 3 ] and its edges are circular arcs and straight ...
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Thin plate splines (TPS) are a spline-based technique for data interpolation and smoothing. "A spline is a function defined by polynomials in a piecewise manner." [1] [2] They were introduced to geometric design by Duchon. [3]