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Journal of the Royal Statistical Society Series B-Statistical Methodology最新文献

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Manifold lifting: scaling Markov chain Monte Carlo to the vanishing noise regime 流形提升:缩放马尔可夫链蒙特卡洛到消失的噪声状态
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-24 DOI: 10.1093/jrsssb/qkad023
K. Au, Matthew M. Graham, Alexandre Hoang Thiery
Standard Markov chain Monte Carlo methods struggle to explore distributions that concentrate in the neighbourhood of low-dimensional submanifolds. This pathology naturally occurs in Bayesian inference settings when there is a high signal-to-noise ratio in the observational data but the model is inherently over-parametrised or nonidentifiable. In this paper, we propose a strategy that transforms the original sampling problem into the task of exploring a distribution supported on a manifold embedded in a higher-dimensional space; in contrast to the original posterior this lifted distribution remains diffuse in the limit of vanishing observation noise. We employ a constrained Hamiltonian Monte Carlo method, which exploits the geometry of this lifted distribution, to perform efficient approximate inference. We demonstrate in numerical experiments that, contrarily to competing approaches, the sampling efficiency of our proposed methodology does not degenerate as the target distribution to be explored concentrates near low-dimensional submanifolds. Python code reproducing the results is available at https://doi.org/10.5281/zenodo.6551654.
标准马尔可夫链蒙特卡罗方法难以探索集中在低维子流形附近的分布。当观测数据的信噪比很高，但模型本身过度参数化或不可识别时，这种病理自然发生在贝叶斯推理设置中。在本文中，我们提出了一种策略，将原始采样问题转化为探索嵌入在高维空间中的流形上支持的分布的任务;与原始后验相反，这种提升的分布在观测噪声消失的极限内保持弥漫性。我们采用约束哈密顿蒙特卡罗方法，利用这种提升分布的几何形状，来执行有效的近似推理。我们在数值实验中证明，与竞争方法相反，我们提出的方法的采样效率不会退化，因为要探索的目标分布集中在低维子流形附近。可从https://doi.org/10.5281/zenodo.6551654获得重现结果的Python代码。
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引用次数: 1
Ordering factorial experiments 排序阶乘实验
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-20 DOI: 10.1093/jrsssb/qkad027
Liuqing Yang, Yongdao Zhou, Min-Qian Liu
In many practical experiments, both the level combinations of factors and the addition orders will affect the responses. However, virtually no construction methods have been provided for such experimental designs. This paper focuses on such experiments, introduces a new type of design called the ordering factorial design, and proposes the nominal main effect component-position model and interaction-main effect component-position model. To obtain efficient fractional designs, we provide some deterministic construction methods. The resulting designs are D-optimal, and the run sizes are much smaller than that of the full designs. Moreover, in some cases, some constructed designs are still D-optimal after reducing the number of components and factors.
在许多实际实验中，因子的水平组合和加成顺序都会影响响应。然而，实际上没有为这种实验设计提供施工方法。本文针对这类实验，提出了一种新型的排序因子设计，并提出了名义主效应成分-位置模型和交互主效应成分-位置模型。为了获得有效的分式设计，我们提供了一些确定性的构造方法。所得到的设计是d最优的，并且运行尺寸比完整设计的运行尺寸小得多。此外，在某些情况下，一些构建的设计在减少组件和因素的数量后仍然是d最优的。
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引用次数: 0
Peter J Bickel, Derek Bean, Aiyou Chen and Purnamrita Sarkar’s contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng Peter J Bickel, Derek Bean, Aiyou Chen和Purnamrita Sarkar对Rohe & Zeng的“Vintage Factor Analysis with Varimax执行统计推断”讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-12 DOI: 10.1093/jrsssb/qkad037
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引用次数: 0
Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation. 对随机试验和真实世界数据进行弹性综合分析，以估计治疗异质性。
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-06 eCollection Date: 2023-07-01 DOI: 10.1093/jrsssb/qkad017
Shu Yang, Chenyin Gao, Donglin Zeng, Xiaofei Wang

We propose a test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilising the trial design, we construct a test to decide whether or not to use real-world data. We characterise the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.

我们提出了一种基于测试的随机试验和真实世界数据的弹性综合分析方法，利用已知效应修饰因子向量来估计治疗效果的异质性。当真实世界数据不存在偏差时，我们的方法将试验数据和真实世界数据结合起来，以进行有效估算。利用试验设计，我们构建了一个测试来决定是否使用真实世界数据。我们描述了基于测试的估计器在局部替代方案下的渐近分布。我们提供了一个数据适应性程序，用于选择测试阈值，该阈值可保证最小的均方误差和具有良好有限样本覆盖特性的弹性置信区间。
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引用次数: 0
Tyler J VanderWeele’s contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng Tyler J VanderWeele对Rohe & Zeng的“Vintage Factor Analysis with variimax演出Statistical Inference”讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-06 DOI: 10.1093/jrsssb/qkad045
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引用次数: 0
Seconder of the vote of thanks to Rohe & Zeng and contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” 其次，感谢Rohe & Zeng对“Vintage Factor Analysis with variimax执行统计推断”的讨论所做的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-06 DOI: 10.1093/jrsssb/qkad031
M. Pensky
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引用次数: 0
Tao Wang’s contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng 王涛对Rohe & Zeng“用方差进行统计推理的复古因子分析”讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-05 DOI: 10.1093/jrsssb/qkad046
T. VanderWeele
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引用次数: 0
Yang Liu’s contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng 杨柳对Rohe & Zeng关于“Vintage Factor Analysis with variimax演出Statistical Inference”的讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-05 DOI: 10.1093/jrsssb/qkad042
Y. Liu
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引用次数: 0
Mark Pilling's contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng Mark Pilling对Rohe & Zeng的“Vintage Factor Analysis with variimax演出Statistical Inference”讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-05 DOI: 10.1093/jrsssb/qkad044
M. Pilling
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引用次数: 0
Rungang Han and Anru R Zhang’s contribution to the Discussion of “Vintage Factor Analysis with Varimax Performs Statistical Inference” by Rohe & Zeng 韩润刚、张安儒对Rohe、Zeng“用方差进行统计推理的复古因子分析”讨论的贡献
IF 5.8 1区 数学 Q1 STATISTICS & PROBABILITY
Journal of the Royal Statistical Society Series B-Statistical Methodology
Pub Date : 2023-04-05 DOI: 10.1093/jrsssb/qkad034
Anru R. Zhang
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引用次数: 0
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