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Large and moderate deviations upper bounds for the Gaussian autoregressive process

✍ Scribed by Julien Worms

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
108 KB
Volume
51
Category
Article
ISSN
0167-7152

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✦ Synopsis

We study the least-squares estimator in the scalar autoregressive model of order 1 with Gaussian noise and arbitrary ΓΏxed initial state. Upper bounds of both large and moderate deviations principles are achieved in the unstable and explosive frameworks. The moderate deviations results are consistent with known results of convergence in distribution of the literature.

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Large and moderate deviations for the empirical measures of an exchangeable sequence
✍ Tryfon Daras πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 451 KB

In this paper we prove large and moderate deviations results for certain sequences of mixtures of probability measures. These results give large and moderate deviations for the empirical measures of an exchangeable sequence. (~) 1997 Elsevier Science B.V.