A Local Procedure for Error Detection and Data Smoothing.

Abstract

In this paper the authors present a local method for data smoothing which is modelled after the manual loft in the ship building industry. The method very effectively solves the outlier problem in statistics, and is superior to the well-known global procedures such as the Schoenberg-Reinsch spline algorithm when it is known that the points have only isolated errors or isolated large errors.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1974
Accession Number
ADA001654

Entities

People

  • R. A. Tapia
  • Victor Guerra

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computing-Related Activities
  • Data Science
  • Detection
  • Engineering
  • Information Science
  • Interdisciplinary Science
  • Manufacturing
  • Mathematics
  • Shipbuilding
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Naval Engineering and Maritime Security