NONLINEAR CONFLUENCE ANALYSIS,

Abstract

Non-linear confluence analysis, necessary for the treatment of experimental data when all variables are subject to errors, is considered from the standpoint of the maximum likelihood method. The likelihood function is a product of curvilinear integrals of the respective distribution densities of each point of the curve. For a sufficiently small curvature and a normal error distribution, these integrals are evaluated approximately, resulting in distribution functions of the normal type but with modified weights and shifted experimental points. Thus, a confluent problem is reduced to an ordinary regressional one. Weight modifications and point shifts may be found by means of successive approximations. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 07, 1964
Accession Number
AD0602579

Entities

People

  • N. P. Klepikov
  • S. N. Sokolov

Organizations

  • National Air and Space Intelligence Center

Tags

DTIC Thesaurus Topics

  • Confluence
  • Curvature
  • Distribution Functions
  • Experimental Data
  • Geometric Forms
  • Geometry
  • Integrals
  • Lines (Geometry)
  • Mathematics

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Calculus or Mathematical Analysis
  • Regression Analysis.