Bayesian analysis of a Poisson process with a change-point
含变点泊松过程的贝叶斯分析AI 解读 ↓
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含变点泊松过程的贝叶斯分析AI 解读 ↓
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A Bayesian approach to estimation and hypothesis testing for a Poisson process with a change-point is developed, and an example given.
伪增量检验:利用自然发生的干预衡量广告增量效应
We develop a method for measuring the incremental effect of advertising when randomized exper- iments are unavailable. Firms generate abrupt interventions in their own marketing as a byproduct of operations: budgets are cut, channels launch, programs pause. We propose a two-stage proce- dure that treats these events as quasi-experiments. The first stage discovers and dates interventions by exact Bayesian run-length inference on marketing activity series. The second stage…
后验漂移下的过度参数化模型
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通过样本加权推断回归中的变点
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In this paper we propose a class of structural vector autoregressions (SVARs) characterized by structural breaks (SVAR-WB). Together with standard restrictions on the parameters and on functions of them, we also consider constraints across the different regimes. Such constraints can be either (a) in the form of stability restrictions, indicating that not all the parameters or impulse responses are subject to structural changes, or (b) in terms of inequalities regarding…
贝叶斯马尔可夫转换部分降秩回归
Reduced-Rank (RR) regression is a powerful dimensionality reduction technique but it overlooks any possible group configuration among the responses by assuming a low-rank structure on the entire coefficient matrix. Moreover, the temporal change of the relations between predictors and responses in time series induce a possibly time-varying grouping structure in the responses. To address these limitations, a Bayesian Markov-switching partial RR (MS-PRR) model is proposed,…