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Statistics - Computational Statistics | Fast Compact Algorithms and Software for Spline Smoothing

Fast Compact Algorithms and Software for Spline Smoothing

Weinert, Howard L.

2013, VIII, 45 p. 7 illus., 5 illus. in color.

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Fast Compact Algorithms and Software for Spline Smoothing investigates algorithmic alternatives for computing cubic smoothing splines when the amount of smoothing is determined automatically by minimizing the generalized cross-validation score. These algorithms are based on Cholesky factorization, QR factorization, or the fast Fourier transform. All algorithms are implemented in MATLAB and are compared based on speed, memory use, and accuracy. An overall best algorithm is identified, which allows very large data sets to be processed quickly on a personal computer.

Content Level » Research

Keywords » Cross-validation - Graduation - Interpolation - Smoothing - Spline

Related subjects » Computational Intelligence and Complexity - Computational Science & Engineering - Computational Statistics - Signals & Communication

Table of contents 

Introduction.- Cholesky Algorithm.- QR Algorithm.- FFT Algorithm.- Discrete Spline Smoothing.

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