activity
20082022
most citedA semiparametric spatial dynamic model

84 citations · 196 across the 11 of their papers we have counts for

collaborators

11 papers

stat.ME2022

A Flexible and Parsimonious Modelling Strategy for Clustered Data Analysis

Tao Huang, Youquan Pei, Jinhong You +1

Statistical modelling strategy is the key for success in data analysis. The trade-off between flexibility and parsimony plays a vital role in statistical modelling. In clustered da…

stat.ME2022

Model Averaging based Semiparametric Modelling for Conditional Quantile Prediction

Chaohui Guo, Wenyang Zhang

In real data analysis, the underlying model is usually unknown, modelling strategy plays a key role in the success of data analysis. Stimulated by the idea of model averaging, we p…

stat.ME2021★ 2 cited

Multi-Kink Quantile Regression for Longitudinal Data with Application to the Progesterone Data Analysis

Chuang Wan, Wei Zhong, Wenyang Zhang +1

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multi-kink quantile regression model for lo…

stat.ME2020★ 1 cited

Estimation and Inference for Multi-Kink Quantile Regression

Wei Zhong, Chuang Wan, Wenyang Zhang

The Multi-Kink Quantile Regression (MKQR) model is an important tool for analyzing data with heterogeneous conditional distributions, especially when quantiles of response variable…

math.ST2017★ 1 cited

Homogeneity Pursuit in Single Index Models based Panel Data Analysis

Heng Lian, Xinghao Qiao, Wenyang Zhang

Panel data analysis is an important topic in statistics and econometrics. Traditionally, in panel data analysis, all individuals are assumed to share the same unknown parameters, e…

stat.ME2016

Factor Models for Asset Returns Based on Transformed Factors

Efang Kong, Jialiang Li, Wenyang Zhang

The Fama-French three factor models are commonly used in the description of asset returns in finance. Statistically speaking, the Fama-French three factor models imply that the ret…