Abstract
One way in which the field of time series analysis develops is by considering processes of increasing complexity, hopefully producing models which can still be analyzed whilst remaining interpretable and useful in applied work. This development is often of a stepping-stone form, with one model naturally evolving into the next or two familiar models merging into something less familiar. The simple autoregressive model of order one
where, throughout, ε t will be taken to be i.i.d. and zero mean, leads immediately to the random walk, by taking a =1 but this change produces a series with dramatically different properties
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© 1996 Springer-Verlag New York, Inc.
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Granger, C.W.J., Hyung, N., Jeon, Y. (1996). Fractional Stochastic Unit Root Processes. In: Robinson, P.M., Rosenblatt, M. (eds) Athens Conference on Applied Probability and Time Series Analysis. Lecture Notes in Statistics, vol 115. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2412-9_14
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DOI: https://doi.org/10.1007/978-1-4612-2412-9_14
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