Search Results for author: Haoyu Wei

Found 8 papers, 1 papers with code

Inference and FDR Control for Simulated Ising Models in High-dimension

no code implementations11 Feb 2022 Haoyu Wei, Xiaoyu Lei, Huiming Zhang

We further propose a decorrelated score test based on the decorrelated score function and prove the asymptotic normality of the score function without the influence of many nuisance parameters under the assumption that accelerates the convergence of the MCMC method.

Asymptotic in a class of network models with an increasing sub-Gamma degree sequence

no code implementations2 Nov 2021 Jing Luo, Haoyu Wei, Xiaoyu Lei, Jiaxin Guo

For the differential privacy under the sub-Gamma noise, we derive the asymptotic properties of a class of network models with binary values with general link function.

Nonparametric Tests of Conditional Independence for Time Series

no code implementations10 Oct 2021 Xiaojun Song, Haoyu Wei

We propose consistent nonparametric tests of conditional independence for time series data.

Time Series

Smooth Tests for Normality in ANOVA

no code implementations10 Oct 2021 Haoyu Wei, Xiaojun Song

In this article, we propose an easy-to-use method to testing the normality assumption in ANOVA models by using smooth tests.

Heterogeneous Overdispersed Count Data Regressions via Double Penalized Estimations

no code implementations7 Oct 2021 Shaomin Li, Haoyu Wei, Xiaoyu Lei

This paper studies the non-asymptotic merits of the double $\ell_1$-regularized for heterogeneous overdispersed count data via negative binomial regressions.

Sharper Sub-Weibull Concentrations: Non-asymptotic Bai-Yin Theorem

no code implementations4 Feb 2021 Huiming Zhang, Haoyu Wei

Arising in high-dimensional probability, non-asymptotic concentration inequalities play an essential role in the finite-sample theory of machine learning and high-dimensional statistics.

Sparse Density Estimation with Measurement Errors

no code implementations14 Nov 2019 Xiaowei Yang, Huiming Zhang, Haoyu Wei, Shouzheng Zhang

It shows that our method has potency and superiority of detecting the shape of multi-mode density compared with other conventional approaches.

Density Estimation

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