4 citations · 12 across the 14 of their papers we have counts for
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Sequential estimation for GEE with adaptive variables and subject selection
Zimu Chen, Zhanfeng Wang, Yuan-chin Ivan Chang
Modeling correlated or highly stratified multiple-response data becomes a common data analysis task due to modern data monitoring facilities and methods. Generalized estimating equ…
Modeling Function-Valued Processes with Nonseparable and/or Nonstationary Covariance Structure
Evandro Konzen, Jian Qing Shi, Zhanfeng Wang
We discuss a general Bayesian framework on modeling multidimensional function-valued processes by using a Gaussian process or a heavy-tailed process as a prior, enabling us to hand…
Distributed sequential method for analyzing massive data
Zhanfeng Wang, Yuan-chin Ivan Chang
To analyse a very large data set containing lengthy variables, we adopt a sequential estimation idea and propose a parallel divide-and-conquer method. We conduct several convention…
Robust functional ANOVA model with t-process
Chen Zhang, Zimu Chen, Zhanfeng Wang +1
Robust estimation approaches are of fundamental importance for statistical modelling. To reduce susceptibility to outliers, we propose a robust estimation procedure with t-process…
A Robust t-process Regression Model with Independent Errors
Wang Zhanfeng, Noh Maengseok, Lee Youngjo +1
Gaussian process regression (GPR) model is well-known to be susceptible to outliers. Robust process regression models based on t-process or other heavy-tailed processes have been d…
Nearly Semiparametric Efficient Estimation of Quantile Regression
Kani Chen, Yuanyuan Lin, Zhanfeng Wang +1
As a competitive alternative to least squares regression, quantile regression is popular in analyzing heterogenous data. For quantile regression model specified for one single quan…
H-relative error estimation approach for multiplicative regression model with random effect
Zhanfeng Wang, Zhuojian Chen, Zimu Chen
Relative error approaches are more of concern compared to absolute error ones such as the least square and least absolute deviation, when it needs scale invariant of output variabl…
A relative error estimation approach for single index model
Zhanfeng Wang, Zimu Chen, Yaohua Wu
A product relative error estimation method for single index regression model is proposed as an alternative to absolute error methods, such as the least square estimation and the le…
Extended T-process Regression Models
Zhanfeng Wang, Jianqing Shi, Youngjo Lee
Gaussian process regression (GPR) model has been widely used to fit data when the regression function is unknown and its nice properties have been well established. In this article…
Least Product Relative Error Estimation
Kani Chen, Yuanyuan Lin, Zhanfeng Wang +1
A least product relative error criterion is proposed for multiplicative regression models. It is invariant under scale transformation of the outcome and covariates. In addition, th…
Evaluating the diagnostic powers of variables and their linear combinations when the gold standard is continuous
Zhanfeng Wang, Yuan-chin Ivan Chang
The receiver operating characteristic (ROC) curve is a very useful tool for analyzing the diagnostic/classification power of instruments/classification schemes as long as a binary-…