Accession Number:

ADA001128

Title:

Spline Functions in Data Analysis.

Descriptive Note:

Technical rept.,

Corporate Author:

PRINCETON UNIV N J DEPT OF STATISTICS

Report Date:

1974-10-01

Pagination or Media Count:

19.0

Abstract:

This paper discusses the approximation of non-exact data by smooth functions. It is shown that optimal approximations for a large class of criteria are spline functions, and that a sub-class of these are resistant to the presence of gross errors in the data. A computational procedure for obtaining the optimal splines is described and illustrated on a set of demographic data. A listing of an APL program implementing the procedure is included.

Subject Categories:

  • Sociology and Law
  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE