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A note on filtering for long memory processes.

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Authors

Thavaneswaran, A
Heyde, C C

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Pergamon-Elsevier Ltd

Abstract

This paper illustrates the use of quasilikelihood methods of inference for a class of possibly long-memory processes such as H-sssi (self-similar stationary increments) processes and long-range dependent sequences. In particular, they can be used in a general derivation without assuming normality of the process; this extends the result of Gripenberg and Norros [1]. Recursive filtering for models with linear intensity is also discussed in some detail.

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Mathematical and Computer Modelling

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Restricted until

2037-12-31
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