57 citations · 91 across the 8 of their papers we have counts for
8 papers
Greedy Forward Regression for Variable Screening
Ming-Yen Cheng, Sanying Feng, Gaorong Li +1
Two popular variable screening methods under the ultra-high dimensional setting with the desirable sure screening property are the sure independence screening (SIS) and the forward…
Efficient estimation in semivarying coefficient models for longitudinal/clustered data
Ming-Yen Cheng, Toshio Honda, Jialiang Li
In semivarying coefficient models for longitudinal/clustered data, usually of primary interest is usually the parametric component which involves unknown constant coefficients. Fir…
Forward variable selection for sparse ultra-high dimensional varying coefficient models
Ming-Yen Cheng, Toshio Honda, Jin-Ting Zhang
Varying coefficient models have numerous applications in a wide scope of scientific areas. While enjoying nice interpretability, they also allow flexibility in modeling dynamic imp…
A New Test for One-Way ANOVA with Functional Data and Application to Ischemic Heart Screening
Jin-Ting Zhang, Ming-Yen Cheng, Chi-Jen Tseng +1
We propose and study a new global test, namely the -test, for the one-way ANOVA problem in functional data analysis. The test statistic is taken as the maximum value of t…
Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data
Ming-Yen Cheng, Toshio Honda, Jialiang Li +1
Ultra-high dimensional longitudinal data are increasingly common and the analysis is challenging both theoretically and methodologically. We offer a new automatic procedure for fin…
Nonparametric and adaptive modeling of dynamic seasonality and trend with heteroscedastic and dependent errors
Yu-Chun Chen, Ming-Yen Cheng, Hau-tieng Wu
Seasonality (or periodicity) and trend are features describing an observed sequence, and extracting these features is an important issue in many scientific fields. However, it is n…