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紧空间上匹配先验的存在性AI 解读

Summary A matching prior at level $1-\alpha$ is a prior such that an associated $1-\alpha$ credible region is also a $1-\alpha$ confidence set. We study the existence of matching priors for general families of credible regions. Our main result gives topological conditions under which matching priors for specific families of credible regions exist. Informally, we prove that, on compact parameter spaces, a matching prior exists if the so-called rejection-probability function…

不平衡类别数据的MCMC计算AI 解读

Many modern applications collect highly imbalanced categorical data, with some categories relatively rare. Bayesian hierarchical models combat data sparsity by borrowing information, while also quantifying uncertainty. However, posterior computation presents a fundamental barrier to routine use; a single class of algorithms does not work well in all settings and practitioners waste time trying different types of Markov chain Monte Carlo (MCMC) approaches. This article was…

用局部近似加速计算密集模型的渐近精确 MCMCAI 解读

We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropolis–Hastings kernel, borrowing ideas from deterministic approximation theory, optimization, and experimental design. Previous efforts at integrating approximate models into…

加州电力备用容量市场的效率AI 解读

Abstract We test the efficiency of the California electricity reserves market by examining systematic differences between its day‐ and hour‐ahead prices. We uncover significant day‐ahead premia, which we attribute to market design characteristics. On the demand side, the market design established a principal–agent relationship between the markets' buyers (principal) and their supervisory authority (agent). The agent had very limited incentives to shift reserve purchases to…

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水平跃迁与经济时间序列中的长记忆假象AI 解读

When applied to time series processes containing occasional level shifts, the log-periodogram (GPH) estimator often erroneously finds long memory. For a stationary short-memory process with a slowly varying level, I show that the GPH estimator is substantially biased, and derive an approximation to this bias. The asymptotic bias lies on the (0, 1) interval, and its exact value depends on the ratio of the expected number of level shifts to a user-defined bandwidth parameter.…

部分重叠时间序列：商品期货波动动态的新模型AI 解读

Abstract In commodity futures markets, contracts with various delivery dates trade simultaneously. Applied researchers typically discard the majority of the data and form a single time series by choosing only one price observation per day. This strategy precludes a full understanding of these markets and can induce complicated nonlinear dynamics in the data. In this paper, I introduce the partially overlapping time series (POTS) model to model jointly all traded contracts.…