An efficient operator for the change point estimation in partial spline model

Sung Won Han, Hua Zhong, Mary Putt

Research output: Contribution to journalArticle

Abstract

In bioinformatics application, the estimation of the starting and ending points of drop-down in the longitudinal data is important. One possible approach to estimate such change times is to use the partial spline model with change points. In order to use estimate change time, the minimum operator in terms of a smoothing parameter has been widely used, but we showed that the minimum operator causes large MSE of change point estimates. In this paper, we proposed the summation operator in terms of a smoothing parameter, and our simulation study showed that the summation operator gives smaller MSE for estimated change points than the minimum one. We also applied the proposed approach to the experiment data, blood flow during photodynamic cancer therapy.

Original languageEnglish
Pages (from-to)1171-1186
Number of pages16
JournalCommunications in Statistics: Simulation and Computation
Volume44
Issue number5
DOIs
Publication statusPublished - 2015 May 7
Externally publishedYes

Fingerprint

Change-point Estimation
Bioinformatics
Splines
Spline
Mathematical operators
Change Point
Blood
Partial
Time Change
Smoothing Parameter
Operator
Summation
Experiments
Point Estimate
Longitudinal Data
Blood Flow
Model
Estimate
Therapy
Cancer

Keywords

  • Change point
  • Nonparametric regression
  • Photodynamic therapy
  • Reproducing kernel Hilbertspace
  • Spline.

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation

Cite this

An efficient operator for the change point estimation in partial spline model. / Han, Sung Won; Zhong, Hua; Putt, Mary.

In: Communications in Statistics: Simulation and Computation, Vol. 44, No. 5, 07.05.2015, p. 1171-1186.

Research output: Contribution to journalArticle

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