4 citations · 6 across the 6 of their papers we have counts for
8 papers
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…
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…
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…
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…
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…
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…