Abstract
A methodology is developed for analysing factorial designs when the observations at a particular treatment combination form a time series. Maximum likelihood estimators of treatment effects and of time series parameters are found. Analogues of the standard F -ratios are proposed for testing treatment effects. A detailed discussion is given for the one-way classification with error variables generated by AR(1) processes. A simulation study for the case of two treatments is presented.
Keywords
- Error Covariance Matrix
- Multivariate Linear Regression Model
- Autoregressive Parameter
- Autocorrelated Error
- Standard ANOVA
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© 1987 D. Reidel Publishing Company
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Sutradhar, B.C., MacNeill, I.B., Sahrmann, H.F. (1987). Time Series Valued Experimental Designs: One-Way Analysis of Variance with Autocorrelated Errors. In: MacNeill, I.B., Umphrey, G.J., Carter, R.A.L., McLeod, A.I., Ullah, A. (eds) Time Series and Econometric Modelling. The University of Western Ontario Series in Philosophy of Science, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4790-0_10
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DOI: https://doi.org/10.1007/978-94-009-4790-0_10
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8624-0
Online ISBN: 978-94-009-4790-0
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