139 citations · 725 across the 72 of their papers we have counts for
6 papers · 2 filters
Optimal Bayesian estimation in random covariate design with a rescaled Gaussian process prior
Debdeep Pati, Anirban Bhattacharya, Guang Cheng
In Bayesian nonparametric models, Gaussian processes provide a popular prior choice for regression function estimation. Existing literature on the theoretical investigation of the…
Gaussian Approximation of General Nonparametric Posterior Distributions
Zuofeng Shang, Guang Cheng
In a general class of Bayesian nonparametric models, we prove that the posterior distribution can be asymptotically approximated by a Gaussian process. Our results apply to nonpara…
A Partially Linear Framework for Massive Heterogeneous Data
Tianqi Zhao, Guang Cheng, Han Liu
We consider a partially linear framework for modelling massive heterogeneous data. The major goal is to extract common features across all sub-populations while exploring heterogen…
Bootstrapping High Dimensional Time Series
Xianyang Zhang, Guang Cheng
This article studies bootstrap inference for high dimensional weakly dependent time series in a general framework of approximately linear statistics. The following high dimensional…
Nonparametric inference in generalized functional linear models
Zuofeng Shang, Guang Cheng
We propose a roughness regularization approach in making nonparametric inference for generalized functional linear models. In a reproducing kernel Hilbert space framework, we const…
Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data
Guang Cheng, Lan Zhou, Jianhua Z. Huang
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be m…