From the 1 of 6 linked papers with an AI index.
6 papers
Specification Testing for Dyadic Regression Models
Ulrich Hounyo, Jiahao Lin, Xiaojun Song
The paper proposes omnibus specification tests for linear conditional‑mean models with undirected dyadic data, introducing a corrected Gaussian bootstrap and Kolmogorov‑Smirnov and…
Paired Sample Tests for High-dimensional Uncorrelatedness via Random Integration
Shiyao Huang, Xiaojun Song
This paper proposes a novel nonparametric test to assess the uncorrelatedness between two high-dimensional random vectors. We develop our test by generalizing the random integratio…
Robust Inference for Dyadic Data with Dependent Ordered Nodes
Ulrich Hounyo, Jiahao Lin, Xiaojun Song
Dyadic regression models are commonly analyzed under the conventional dyadic dependence framework, where two observations may be dependent only if the corresponding dyads share a n…
Testing Heteroskedasticity Under Measurement Error
Xiaojun Song, Jichao Yuan
In this paper, we propose a novel approach to detect heteroskedasticity in regression models with regressors contaminated by measurement error. Specifically, inspired by the integr…
Data-driven Smooth Tests for Normality in ANOVA When the Number of Groups is Large
Peiwen Jia, Xiaojun Song, Haoyu Wei
The normality assumption for random errors is fundamental in the analysis of variance (ANOVA) models. However, it is rarely subjected to formal testing in practice, and theoretical…
Unified Inference on Moment Restrictions with Nuisance Parameters
Xingyu Li, Xiaojun Song, Zhenting Sun
This paper proposes a simple unified inference approach on moment restrictions in the presence of nuisance parameters. The proposed test is constructed based on a new characterizat…