In this paper we consider first-order autoregressive processes and we allow either centered Normal or exponential innovations. We prove large deviation principles for posterior distributions on the unknown parameter and, motivated by potential applications in risk theory, we also prove large deviation principles for Bayesian estimators of Lundberg’s parameter.
Macci, C. (2010). Large deviations for Bayesian estimators in first-order autoregressive processes. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 140(9), 2790-2797 [10.1016/j.jspi.2010.02.023].
Large deviations for Bayesian estimators in first-order autoregressive processes
MACCI, CLAUDIO
2010-01-01
Abstract
In this paper we consider first-order autoregressive processes and we allow either centered Normal or exponential innovations. We prove large deviation principles for posterior distributions on the unknown parameter and, motivated by potential applications in risk theory, we also prove large deviation principles for Bayesian estimators of Lundberg’s parameter.File in questo prodotto:
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