19 citations · 39 across the 8 of their papers we have counts for
9 papers
Panel Data Models with Time-Varying Latent Group Structures
Yiren Wang, Peter C B Phillips, Liangjun Su
This paper considers a linear panel model with interactive fixed effects and unobserved individual and time heterogeneities that are captured by some latent group structures and an…
Low-rank Panel Quantile Regression: Estimation and Inference
Yiren Wang, Liangjun Su, Yichong Zhang
In this paper, we propose a class of low-rank panel quantile regression models which allow for unobserved slope heterogeneity over both individuals and time. We estimate the hetero…
A One-Covariate-at-a-Time Method for Nonparametric Additive Models
Liangjun Su, Thomas Tao Yang, Yonghui Zhang +1
This paper proposes a one-covariate-at-a-time multiple testing (OCMT) approach to choose significant variables in high-dimensional nonparametric additive regression models. Similar…
Interactive Effects Panel Data Models with General Factors and Regressors
Bin Peng, Liangjun Su, Joakim Westerlund +1
This paper considers a model with general regressors and unobservable factors. An estimator based on iterated principal components is proposed, which is shown to be not only asympt…
L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis
Zhentao Shi, Liangjun Su, Tian Xie
This paper tackles forecast combination with many forecasts or minimum variance portfolio selection with many assets. A novel convex problem called L2-relaxation is proposed. In co…
Detecting Latent Communities in Network Formation Models
Shujie Ma, Liangjun Su, Yichong Zhang
This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed e…
Determining the Number of Communities in Degree-corrected Stochastic Block Models
Shujie Ma, Liangjun Su, Yichong Zhang
We propose to estimate the number of communities in degree-corrected stochastic block models based on a pseudo likelihood ratio statistic. To this end, we introduce a method that c…
Strong Consistency of Spectral Clustering for Stochastic Block Models
Liangjun Su, Wuyi Wang, Yichong Zhang
In this paper we prove the strong consistency of several methods based on the spectral clustering techniques that are widely used to study the community detection problem in stocha…
Non-separable Models with High-dimensional Data
Liangjun Su, Takuya Ura, Yichong Zhang
This paper studies non-separable models with a continuous treatment when the dimension of the control variables is high and potentially larger than the effective sample size. We pr…