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 language | English |
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Pages (from-to) | 1171-1186 |
Number of pages | 16 |
Journal | Communications in Statistics: Simulation and Computation |
Volume | 44 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2015 May 7 |
Externally published | Yes |
Bibliographical note
Funding Information:The research was supported by NIH-NCI 5-P01-CA-087971.
Publisher Copyright:
© 2015 Taylor & Francis Group, LLC.
Keywords
- Change point
- Nonparametric regression
- Photodynamic therapy
- Reproducing kernel Hilbertspace
- Spline.
ASJC Scopus subject areas
- Statistics and Probability
- Modelling and Simulation