The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions

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Tác giả: Noa Kallioinen, David Kohns, Yann McLatchie, Aki Vehtari

Ngôn ngữ: eng

Ký hiệu phân loại: 511.4 Approximations formerly also 513.24 and expansions

Thông tin xuất bản: 2024

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 202824

We present the ARR2 prior, a joint prior over the auto-regressive components in Bayesian time-series models and their induced $R^2$. Compared to other priors designed for times-series models, the ARR2 prior allows for flexible and intuitive shrinkage. We derive the prior for pure auto-regressive models, and extend it to auto-regressive models with exogenous inputs, and state-space models. Through both simulations and real-world modelling exercises, we demonstrate the efficacy of the ARR2 prior in improving sparse and reliable inference, while showing greater inference quality and predictive performance than other shrinkage priors. An open-source implementation of the prior is provided.
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