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Abstract. Within the context of likelihood and Bayes approaches to inference in autoregressive moving‐average (ARMA) time series models, previous ideas on parameter transformation and numerical integration for implementing Bayesian procedures are reviewed. Some novel transformation ideas are introduced and their role in an efficient numerical integration approach is examined. Some comparisons of the effectivesness of different numerical integration strategies are made.
Marriott et al. (Wed,) studied this question.