Search Results for author: Harold D. Chiang

Found 7 papers, 0 papers with code

On the Inconsistency of Cluster-Robust Inference and How Subsampling Can Fix It

no code implementations20 Aug 2023 Harold D. Chiang, Yuya Sasaki, Yulong Wang

Conventional methods of cluster-robust inference are inconsistent in the presence of unignorably large clusters.

valid

Inference in high-dimensional regression models without the exact or $L^p$ sparsity

no code implementations21 Aug 2021 Jooyoung Cha, Harold D. Chiang, Yuya Sasaki

This paper proposes a new method of inference in high-dimensional regression models and high-dimensional IV regression models.

regression

Algorithmic subsampling under multiway clustering

no code implementations28 Feb 2021 Harold D. Chiang, Jiatong Li, Yuya Sasaki

This paper proposes a novel method of algorithmic subsampling (data sketching) for multiway cluster dependent data.

Clustering

Linear programming approach to nonparametric inference under shape restrictions: with an application to regression kink designs

no code implementations12 Feb 2021 Harold D. Chiang, Kengo Kato, Yuya Sasaki, Takuya Ura

We develop a novel method of constructing confidence bands for nonparametric regression functions under shape constraints.

regression

Empirical likelihood and uniform convergence rates for dyadic kernel density estimation

no code implementations17 Oct 2020 Harold D. Chiang, Bing Yang Tan

This paper studies the asymptotic properties of and alternative inference methods for kernel density estimation (KDE) for dyadic data.

Clustering Density Estimation

Inference for high-dimensional exchangeable arrays

no code implementations10 Sep 2020 Harold D. Chiang, Kengo Kato, Yuya Sasaki

We consider inference for high-dimensional separately and jointly exchangeable arrays where the dimensions may be much larger than the sample sizes.

Density Estimation regression +1

Many Average Partial Effects: with An Application to Text Regression

no code implementations21 Dec 2018 Harold D. Chiang

We study estimation, pointwise and simultaneous inference, and confidence intervals for many average partial effects of lasso Logit.

regression valid

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