On jackknife, cross-validatory and classical methods of estimating a proportion with batches of different sizes

Some properties of a proposed jackknife estimator of a proportion from batches of different sizes are exposed. Alternative ‘computer-intensive’ estimators are devised which, together with some ‘classical’ estimators, are then compared in a simulation study of their mean squared errors and the coverage and expected length of their associated confidence intervals.

摘要来源：OpenAlex 索引摘要（稿件版本未注明）

笔记与分组

同方向的基础文献

相关领域论文

共同方法：检验与推断、一般估计

Bootstrap inference in factor-augmented regressions with weak factors

Peiyun Jiang · Takashi Yamagata首次提交 2025-10-01 · 修订 2026-10-14 · v2arXiv预印本

In this paper, we develop bootstrap methods for factor-augmented regressions with potentially weak common components, allowing signal eigenvalues to diverge at heterogeneous rates $N^{α_k}$, where $0<α_k\leq1$, $k=1,\ldots,r$. The regression estimator targets a rotation of the latent parameter vector that may be data dependent, while factor estimation can induce asymptotic bias. The proposed procedure directly constructs the rotation-specific target in the bootstrap world,…

金融 · 金融因子 Bootstrap 与重抽样金融 · 收益预测

被引：暂无数据

阅读原文 ↗BibTeX ↓

共同方法：检验与推断、一般估计

Testing Conditional Distribution Equality Using Generative Models

Zekai Jin · Yi Zhang · Yun Yang · Xiaofeng Shao首次提交 2026-10-14 · 修订 2026-10-14 · v1arXiv预印本

使用生成模型检验条件分布相等AI 解读

Conditional distribution equality testing is a core problem with applications in causal inference, model diagnostics, and transfer learning. Existing methods often lose power when the conditioning variable is high-dimensional. We propose a new test that leverages generative models to compare conditional distributions using both observed data and synthetic samples. A sample-splitting and studentization scheme is introduced to control estimation error. Under the null, the test…

微观 · 因果推断高维与机器学习核、筛与局部多项式

被引：暂无数据

AI 解读阅读原文 ↗BibTeX ↓

共同方法：检验与推断、一般估计

Propensity score with factor loadings: evaluating the effect of the Paris Agreement on the returns of European stocks

Angelo Forino · Andrea Mercatanti · Giacomo Morelli首次提交 2025-07-11 · 修订 2026-10-14 · v2arXiv预印本

Factor models for longitudinal data, where policy adoption is unconfounded with respect to a low-dimensional set of latent factor loadings, have become increasingly popular for causal inference. Most existing approaches, however, rely on a causal finite-sample approach or computationally intensive methods, limiting their applicability and external validity. In this paper, we propose a novel method for panel causal inference within a super-population framework, based on…

微观 · 因果推断微观 · 面板数据金融 · 金融因子

被引：暂无数据

阅读原文 ↗BibTeX ↓

共同方法：检验与推断、一般估计

Two Gaussians, Too Many: A bootstrap-based approach to assess identifiability in non-Gaussian structural vector autoregressions

Paritosh Shankarrao Junare首次提交 2026-07-19 · 修订 2026-10-14 · v2arXiv预印本

Normality pre-tests on reduced-form innovations cannot detect whether two or more underlying structural shocks are Gaussian, and hence cannot detect a failure of identification in non-Gaussian SVARs. We propose a bootstrap-based approach that reveals such a failure. Under the null of valid identification and certain regularity conditions, the conditional bootstrap distribution of the maximum likelihood estimator of the impact matrix is asymptotically normal, so the…

宏观 · 时间序列 Bootstrap 与重抽样极大与准极大似然

关联记录被引 0 次 ↗OpenAlex · 核验 2026-10-15

阅读原文 ↗BibTeX ↓

共同方法：检验与推断、一般估计

Controlling the false discovery rate in high-dimensional linear models using model-X knockoffs and $p$-values

Jinyuan Chang · Chenlong Li · Cheng Yong Tang · Zhengtian Zhu首次提交 2025-05-22 · 修订 2026-10-14 · v3arXiv预印本

结合 model-X knockoffs 与 p 值的高维线性模型 FDR 控制AI 解读

We propose a novel multiple testing methodology for controlling the false discovery rate (FDR) in high-dimensional linear models that integrates model-X knockoff techniques with debiased penalized regression estimators. At the foundation of our methodology, we construct and study two sets of naturally paired high-dimensional test statistics and the associated $p$-values for evaluating the same null hypotheses. The first set is shown to be asymptotically mutually independent,…

多重检验与同时推断正则化与变量选择

关联记录被引 0 次 ↗OpenAlex · 核验 2026-10-14

AI 解读阅读原文 ↗BibTeX ↓

共同方法：检验与推断、一般估计

Principal stratification with continuous treatments and continuous post-treatment variables

Joseph Antonelli · Minxuan Wu · Fabrizia Mealli · Brenden Beck · Alessandra Mattei首次提交 2023-09-25 · 修订 2026-10-14 · v3arXiv预印本

Principal stratification (PS) is a commonly used approach for understanding the mechanisms through which a treatment affects an outcome. The goal of this work is to extend the PS framework to studies with continuous treatments, which introduces a number of both challenges and opportunities in terms of defining causal effects and performing inference. This manuscript provides multiple key methodological contributions: 1) we introduce principal causal estimands for continuous…

微观 · 因果推断半参数与非参数贝叶斯

关联记录被引 2 次 ↗OpenAlex · 核验 2026-09-30

阅读原文 ↗BibTeX ↓