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  2. Inverse distance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_distance_weighting

    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.

  3. Natural-neighbor interpolation - Wikipedia

    en.wikipedia.org/wiki/Natural-neighbor_interpolation

    Natural neighbor interpolation with Sibson weights. The area of the green circles are the interpolating weights, w i.The purple-shaded region is the new Voronoi cell, after inserting the point to be interpolated (black dot).

  4. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Inverse distance weighting; Radial basis function (RBF) — a function of the form ƒ(x) = φ(|x−x 0 |) Polyharmonic spline — a commonly used radial basis function; Thin plate spline — a specific polyharmonic spline: r 2 log r; Hierarchical RBF; Subdivision surface — constructed by recursively subdividing a piecewise linear interpolant

  5. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    Inverse distance weighting; ABOS - approximation based on smoothing; Kriging; Gradient-enhanced kriging (GEK) Thin plate spline; Polyharmonic spline (the thin-plate-spline is a special case of a polyharmonic spline) Radial basis function (Polyharmonic splines are a special case of radial basis functions with low degree polynomial terms) Least ...

  6. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    Compute the Euclidean or Mahalanobis distance from the query example to the labeled examples. Order the labeled examples by increasing distance. Find a heuristically optimal number k of nearest neighbors, based on RMSE. This is done using cross validation. Calculate an inverse distance weighted average with the k-nearest multivariate neighbors.

  7. Geostatistics - Wikipedia

    en.wikipedia.org/wiki/Geostatistics

    A number of simpler interpolation methods/algorithms, such as inverse distance weighting, bilinear interpolation and nearest-neighbor interpolation, were already well known before geostatistics. [2] Geostatistics goes beyond the interpolation problem by considering the studied phenomenon at unknown locations as a set of correlated random variables.

  8. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    Application areas of kernel methods are diverse and include geostatistics, [8] kriging, inverse distance weighting, 3D reconstruction, bioinformatics, cheminformatics, information extraction and handwriting recognition.

  9. Inverse probability weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_probability_weighting

    Inverse probability weighting is a statistical technique for estimating quantities related to a population other than the one from which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application. [ 1 ]