Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Lei, Lihua"'
We introduce a generic estimator for the false discovery rate of any model selection procedure, in common statistical modeling settings including the Gaussian linear model, Gaussian graphical model, and model-X setting. We prove that our method has a
Externí odkaz:
http://arxiv.org/abs/2408.07231
Autor:
Lei, Lihua
In studies of educational production functions or intergenerational mobility, it is common to transform the key variables into percentile ranks. Yet, it remains unclear what the regression coefficient estimates with ranks of the outcome or the treatm
Externí odkaz:
http://arxiv.org/abs/2406.05548
We introduce Bellman Conformal Inference (BCI), a framework that wraps around any time series forecasting models and provides approximately calibrated prediction intervals. Unlike existing methods, BCI is able to leverage multi-step ahead forecasts a
Externí odkaz:
http://arxiv.org/abs/2402.05203
Autor:
Lei, Lihua, Sudijono, Timothy
The synthetic control method is often applied to problems with one treated unit and a small number of control units. A common inferential task in this setting is to test null hypotheses regarding the average treatment effect on the treated. Inference
Externí odkaz:
http://arxiv.org/abs/2401.07152
Autor:
Lei, Lihua, Ross, Brad
We develop a new, spectral approach for identifying and estimating average counterfactual outcomes under a low-rank factor model with short panel data and general outcome missingness patterns. Applications include event studies and studies of outcome
Externí odkaz:
http://arxiv.org/abs/2312.07520
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. We provide a framework to choose the clustering that minimizes the worst-case mean-squared error of the estimated glob
Externí odkaz:
http://arxiv.org/abs/2310.14983
Many causal estimands are only partially identifiable since they depend on the unobservable joint distribution between potential outcomes. Stratification on pretreatment covariates can yield sharper partial identification bounds; however, unless the
Externí odkaz:
http://arxiv.org/abs/2310.08115
Inferring variable importance is the key problem of many scientific studies, where researchers seek to learn the effect of a feature $X$ on the outcome $Y$ in the presence of confounding variables $Z$. Focusing on classification problems, we define t
Externí odkaz:
http://arxiv.org/abs/2309.04002
Autor:
Gu, Zhenjie, Xie, Zhangning, Chang, Zhikun, Xiao, Guangxu, Yin, Zhijun, Lin, Zichao, Zhou, Tong, Lei, Lihua, Jin, Tao, Xue, Dongbai, Deng, Xiao, Chen, Xinbin, Li, Tongbao
Traceability of precision instrument and measuring method is the core issue in metrology science. In the field of nanometer length measurement, the laser interferometers are usually used to trace the measurement value to the laser wavelength, but the
Externí odkaz:
http://arxiv.org/abs/2306.14146
Autor:
Lin, Zichao, Yao, Yulin, Xie, Zhangning, Xue, Dongbai, Zhou, Tong, Tang, Zhaohui, Lei, Lihua, Jin, Tao, Dun, Xiong, Deng, Xiao, Cheng, Xinbin, Li, Tongbao
Natural constant-based metrology methods offer an effective approach to achieving traceability in nanometric measurements. The Cr grating, fabricated by atom lithography and featuring a pitch of $d=212.7705\pm0.0049~{\rm nm}$ traceable to the Cr tran
Externí odkaz:
http://arxiv.org/abs/2306.14083