Non-Parametric Regression or Smoothing on a Two Dimensional Lattice Using the K-Matrix

Authors: Stephen P. Smith

A two-dimensional lattice model is described that is able to treat border effects in a coherent way. The model belongs to a class of non-parametric regression models, coming with three smoothness parameters that are estimated from cross validation. The techniques use the K-matrix, which is a typically large and sparse matrix that is also symmetric and indefinite. The K-matrix is subjected to factorization, and algorithmic differentiation, using optimized software, thereby permitting estimation of the smoothness parameters and estimation of the two-dimensional surface. The techniques are demonstrated on real data.

Comments: 16 Pages.

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Submission history

[v1] 2018-12-03 23:59:55 (removed)
[v2] 2018-12-06 23:22:48 (removed)
[v3] 2018-12-08 01:40:57

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