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20242026
most citedAnother Look at Bandwidth-free Inference: a Sample Splitting Approach

4 citations · 7 across the 9 of their papers we have counts for

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8 papers · 1 filter

math.CO2026

Intersecting families of loose spanning hypertrees

Yury Person, Thomas Schweser

A loose hypertree is a hypergraph whose incidence graph is a tree. Let , , and . We determine the largest -intersecting families of lo…

stat.ML2026

Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning under Markovian Sampling

Min Zeng, Yichen Zhang, Xiaofeng Shao

Constant-stepsize temporal-difference (TD) learning is attractive for policy evaluation, but inference from a single Markov trajectory must account for serial dependence and a step…

stat.ME2026

Testing Equality of Conditional Distributions via Generative Models

Hanjia Gao, Linjun Huang, Yun Yang +1

We study the problem of testing whether two conditional distributions are equal using generative models. The proposed method learns a conditional generator from each sample and use…

stat.ME2026★ 2 cited

Hypothesis Testing for a Functional Parameter via Self-normalization

Yi Zhang, Xiaofeng Shao

Testing simple or composite hypothesis on a functional parameter has attracted considerable attention in time series analysis. To accommodate for the unknown temporal dependence, c…

stat.ME2026★ 4 cited

Another Look at Bandwidth-free Inference: a Sample Splitting Approach

Yi Zhang, Xiaofeng Shao

The bandwidth-free tests/inferences for a multi-dimensional parameter have attracted considerable attention in econometrics and statistics literature. These tests can be convenient…

stat.ME2026★ 1 cited

Change-Point Detection for Object-valued Time Series

Yi Zhang, Changbo Zhu, Xiaofeng Shao

This article is concerned with change point detection for object-valued data that reside in a metric space, which has attracted some recent interests in statistics and econometrics…

econ.EM2026

Generalized Spectral Testing with Sample Splitting

Yuxin Tao, Feiyu Jiang, Xiaofeng Shao

Residual-based goodness-of-fit tests for parametric time-series models are often complicated by parameter-estimation effects, which can alter the limiting behavior of diagnostic st…

stat.ME2026

Resampling-free Inference for Time Series via RKHS Embedding

Deep Ghoshal, Xiaofeng Shao

In this article, we study nonparametric inference problems in the context of multivariate or functional time series, including testing for goodness-of-fit, the presence of a change…