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- Title
Bent-cable regression with autoregressive noise.
- Authors
Chiu, Grace S.; Lockhart, Richard A.
- Abstract
Motivated by time series of atmospheric concentrations of certain pollutants the authors develop bent-cable regression for autocorrelated errors. Bent-cable regression extends the popular piecewise linear (broken-stick) model, allowing for a smooth change region of any non-negative width. Here the authors consider autoregressive noise added to a bent-cable mean structure, with unknown regression and time series parameters. They develop asymptotic theory for conditional least-squares estimation in a triangular array framework, wherein each segment of the bent cable contains an increasing number of observations while the autoregressive order remains constant as the sample size grows. They explore the theory in a simulation study, develop implementation details, apply the methodology to the motivating pollutant dataset, and provide a scientific interpretation of the bent-cable change point not discussed previously.
- Subjects
REGRESSION analysis; MAXIMUM likelihood statistics; LEAST squares; AUTOREGRESSION (Statistics); STATISTICS
- Publication
Canadian Journal of Statistics, 2010, Vol 38, Issue 3, p386
- ISSN
0319-5724
- Publication type
Article
- DOI
10.1002/cjs.10070