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Activity Number:
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339
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Type:
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Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #306507 |
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Title:
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Bent-Cable Regression with Autoregressive Noise
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Author(s):
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Grace Chiu*+ and Richard Lockhart
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Companies:
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University of Waterloo and Simon Fraser University
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Address:
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Department of Statistics and Actuarial Science, Waterloo, ON, N2L 3G1, Canada
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Keywords:
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autoregressive ; bent-cable regression ; change-point ; time series
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Abstract:
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Bent-cable regression extends the popular piecewise linear (broken-stick) model, allowing for a smooth change region of any non-negative width. Existing bent-cable methodology assumes independent and identically distributed errors. In this talk, we investigate data that exhibit a bent-cable mean structure with noise generated by a low order autoregressive model. We suggest a somewhat unusual approach for developing asymptotics of both regression and time series parameter estimators. Preliminary results based on simulations and physiological and atmospheric datasets are presented.
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