Analysis of Two Advanced Smoothing Algorithms.

Abstract

This thesis examines two smoothing algorithms which deviate from the classical method of using only one neighborhood size in the smoothing procedure. The Supersmooth algorithm uses three neighborhood sizes with local cross-validation in order to estimate an optimal neighborhood size. The Split Linear Fit algorithm uses any number of neighborhood sizes and computes a family of linear fits corresponding to each neighborhood size; the final smooth points are a weighted average of the linear fits. These two advanced smoothers are evaluated against the results produced by previously validated, commonly used smoothers and regression techniques. The measure of performance is the quality of the smooth curves and the value of the sum of squared residuals. Keywords: Test and evaluation; Computer programs; and Subroutines. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1985
Accession Number
ADA162305

Entities

People

  • Jose A. Vasquez Jr

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Central Processing Units
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Analysis
  • Digital Information
  • Information Science
  • Linear Accelerators
  • Operations Research
  • Procedures (Computers)
  • Sea Surface Temperature
  • Surface Temperature
  • Terminals
  • Test And Evaluation
  • United States

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Regression Analysis.