LAD Spline Fitting

  • Peter Bloomfield
  • William L. Steiger
Part of the Progress in Probability and Statistics book series (PRPR, volume 6)


Polynomial spline functions are useful in numerical approximation and smoothing. Their use for smoothing of statistical data was first described by Schoenberg (1964). Several authors have pursued these ideas [e.g. Reinsch (1967, 1971); Wahba (1976); Utreras (1981b)]. The use of splines to be described in this chapter is closely related to the robust splines described by Huber (1979). Utreras (1981a) has discussed a similar problem, also using the term “robust splines”, though somewhat inappropriately for statisticians, since his work is centered around the use of the discrete L norm.


Conditional Distribution Regression Quantile Spline Function Nonparametric Regression Constraint Force 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Birkhäuser Boston, Inc. 1983

Authors and Affiliations

  • Peter Bloomfield
    • 1
  • William L. Steiger
    • 2
  1. 1.Department of StatisticsNorth Carolina State UnversityRaleighUSA
  2. 2.Department of Computer ScienceRutgers UniversityNew BrunswickUSA

Personalised recommendations