Chengchun Shi

Works (11)

Updated: March 25th, 2024 08:09

2023 journal article

Deep spectral Q-learning with application to mobile health

STAT, 12(1).

By: Y. Gao  n, C. Shi* & R. Song n 

author keywords: dynamic treatment regimes; mixed frequency data; principal component analysis; reinforcement learning
TL;DR: A deep spectral Q‐learning algorithm is proposed, which integrates principal component analysis (PCA) with deep Q‐learning to handle the mixed frequency data and proves that the mean return under the estimated optimal policy converges to that under the optimal one and establishes its rate of convergence. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: May 15, 2023

2021 journal article

Concordance and Value Information Criteria for Optimal Treatment Decision

Annals of Statistics, 49(1), 49–75.

By: C. Shi*, R. Song n  & W. Lu n

author keywords: Concordance and value information criteria; optimal treatment regime; tuning parameter selection; variable selection
TL;DR: This paper studies two information criteria: the concordance and value information criteria, for variable selection in optimal treatment decision making, and considers both fixed-$p$ and high dimensional settings, and shows they are consistent in model/tuning parameter selection. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: March 22, 2021

2021 article

Statistical inference of the value function for reinforcement learning in infinite-horizon settings

Shi, C., Zhang, S., Lu, W., & Song, R. (2021, December 22). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, Vol. 12.

By: C. Shi*, S. Zhang n, W. Lu n & R. Song n 

author keywords: bidirectional asymptotics; confidence interval; infinite horizons; reinforcement learning; value function
TL;DR: The focus of this paper was to construct confidence intervals (CIs) for a policy’s value in infinite horizon settings where the number of decision points diverges to infinity and it is shown that the proposed CI achieves nominal coverage even in cases where the optimal policy is not unique. (via Semantic Scholar)
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16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: January 3, 2022

2020 journal article

Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 116(535), 1307–1318.

By: C. Shi*, R. Song n , W. Lu n & R. Li *

author keywords: Confidence interval; Generalized linear models; Online estimation; Ultrahigh dimensions
TL;DR: A new estimation and valid inference method for single or low-dimensional regression coefficients in high-dimensional generalized linear models and it is proved the proposed CI is asymptotically narrower than the CIs constructed based on the desparsified Lasso estimator and the decorrelated score statistic. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: February 10, 2020

2019 journal article

A Sparse Random Projection-Based Test for Overall Qualitative Treatment Effects

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 115(531), 1201–1213.

By: C. Shi n, W. Lu n & R. Song n 

author keywords: High-dimensional testing; Optimal treatment regime; Precision medicine; Qualitative treatment effects; Sparse random projection
TL;DR: This article considers testing the overall qualitative treatment effects of patients’ prognostic covariates in a high-dimensional setting and proposes a sample splitting method to construct the test statistic, based on a nonparametric estimator of the contrast function. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: July 29, 2019

2019 journal article

LINEAR HYPOTHESIS TESTING FOR HIGH DIMENSIONAL GENERALIZED LINEAR MODELS

ANNALS OF STATISTICS, 47(5), 2671–2703.

By: C. Shi n, R. Song n , Z. Chen  n & R. Li  n

author keywords: High dimensional testing; linear hypothesis; likelihood ratio statistics; score test; Wald test
TL;DR: This paper proposes constrained partial regularization method and introduces an algorithm for solving regularization problems with folded-concave penalty functions and linear constraints, and shows that the limiting null distributions of these three test statistics are χ2 distribution with the same degrees of freedom, and under local alternatives, they asymptotically follow non-central χ1 distribution. (via Semantic Scholar)
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16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 19, 2019

2019 journal article

ON TESTING CONDITIONAL QUALITATIVE TREATMENT EFFECTS

ANNALS OF STATISTICS, 47(4), 2348–2377.

By: C. Shi n, R. Song n  & W. Lu n

TL;DR: The proposed definition of CQTE does not assume any parametric form for the optimal treatment rule and plays an important role for assessing the incremental value of a set of new variables in optimal treatment decision making conditional on an existing set of prescriptive variables. (via Semantic Scholar)
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3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: June 17, 2019

2018 journal article

Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 80(4), 681–702.

By: C. Shi n, R. Song* , W. Lu n & B. Fu  n

author keywords: Heterogeneity; Maximin projection learning; Optimal treatment regime; Quadratically constrained linear programming
TL;DR: A new maximin projection learning method is proposed for estimating a single treatment decision rule that works reliably for a group of future patients from a possibly new subpopulation by solving a quadratically constrained linear programming problem, which can be efficiently computed by interior point methods. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries
Added: October 19, 2018

2017 journal article

A Massive Data Framework for M-Estimators with Cubic-Rate

Journal of the American Statistical Association, 113(524), 1698–1709.

By: C. Shi n, W. Lu n & R. Song n 

author keywords: Cubic rate asymptotics; Divide and conquer; M-estimators; Massive data
TL;DR: Under certain condition on the growing rate of the number of subgroups, the resulting aggregated estimators are shown to have faster convergence rate and asymptotic normal distribution, which are more tractable in both computation and inference than the original M-estimators based on pooled data. (via Semantic Scholar)
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Sources: Web Of Science, NC State University Libraries, Crossref
Added: February 18, 2019

2016 journal article

Robust learning for optimal treatment decision with NP-dimensionality

ELECTRONIC JOURNAL OF STATISTICS, 10(2), 2894–2921.

By: C. Shi n, R. Song n  & W. Lu n

author keywords: Non-concave penalized likelihood; optimal treatment strategy; oracle property; variable selection
TL;DR: A robust procedure for estimating the optimal treatment regime under NP dimensionality is proposed and penalized regressions are employed with the non-concave penalty function, where the conditional mean model of the response given predictors may be misspecified. (via Semantic Scholar)
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16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2016 journal article

simplexreg: An R package for regression analysis of proportional data using the simplex distribution

Journal of Statistical Software, 71(11), 1–21.

By: P. Zhang, Z. Qiu & C. Shi

Source: NC State University Libraries
Added: August 6, 2018

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