A Least Squares Algorithm for Fitting Piecewise Linear Functions on Fixed Domains.

Abstract

A least squared error algorithm is presented for fitting a piecewise linear function to observed data, when the slope of the function is allowed to change only at specified points. The algorithm can be used to estimate piecewise linear trends in data, where the locations of possible changes in trend are known. Furthermore, it can be used to reduce large quantities of data to manageable sizes. In addition, the algorithm is robust to problems of data dropout provided it is used cautiously. An example of a possible application is the fitting of a linear segment bathythermal profile (temperature vs. depth) to a large quantity of data. Keywords: Canada; underwater acoustics; linear regression; numerical analysis. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1985
Accession Number
ADA161870

Entities

People

  • B. A. Trenholm

Organizations

  • Defence Research and Development Canada

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Acoustics
  • Algorithms
  • Classification
  • Curve Fitting
  • Data Sets
  • Extrapolation
  • Interpolation
  • Least Squares Method
  • Linear Programming
  • National Security
  • Numerical Analysis
  • Security
  • Simplex Method
  • Standards
  • Temperature Gradients
  • Underwater Acoustics

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.