Zhonghua Li

发表

A generally weighted moving average control chart for monitoring the coefficient of variation

Zhonghua Li, Rui Chen, Jiujun Zhang, 2019, Applied Mathematical Modelling.

On-line monitoring data quality of high-dimensional data streams

Zhonghua Li, Zhaojun Wang, Dequan Qi, 2016 .

Multivariate Exponentially Weighted Moving-Average Chart for Monitoring Poisson Observations

Nan Chen, Zhonghua Li, Yanjing Ou, 2015 .

The computation of average run length and average time to signal: an overview

Changliang Zou, Zhonghua Li, Zhaojun Wang, 2014 .

A Phase II control chart based on the weighted likelihood ratio test for monitoring polynomial profiles

Zhonghua Li, Jiujun Zhang, Cailian Yao, 2020 .

A robust variable screening method for high-dimensional data

Zhonghua Li, Tao Wang, Linbiao Zheng, 2017 .

Multiple outliers detection in sparse high-dimensional regression

Bin Chen, Zhonghua Li, Qun Li, 2018 .

Outlier detection in high-dimensional regression model

Zhonghua Li, Tao Wang, 2017 .

False discovery rates for large-scale model checking under certain dependence

Zhonghua Li, Xuemin Zi, Lu Deng, 2018 .

A weighted likelihood ratio test-based chart for monitoring process mean and variability

Zhonghua Li, Jiujun Zhang, Zhi Song, 2018 .

Using p values to design statistical process control charts

Zhaojun Wang, Snigdhansu Chatterjee, P. Qiu, 2012, Statistical Papers.

Monitoring of Linear Profiles Using Linear Mixed Model in the Presence of Measurement Errors

Zhaojun Wang, Zhonghua Li, Wenhui Liu, 2022, Mathematics.

On Nonparametric Statistical Process Control of Univariate Processes

Peihua Qiu, Zhonghua Li, P. Qiu, 2011, Technometrics.

Determining the number of change‐point via high‐dimensional cross‐validation

Haiyan Jiang, Jiaqi Li, Zhonghua Li, 2020, Stat.

Multivariate Change Point Control Chart Based on Data Depth for Phase I Analysis

Zhonghua Li, Yi Dai, Zhaojun Wang, 2014, Commun. Stat. Simul. Comput..

A multiple-case deletion approach for detecting influential points in high-dimensional regression

Tao Wang, Qun Li, Zhonghua Li, 2019, Commun. Stat. Simul. Comput..

A comparative study of memory‐type control charts based on robust scale estimators

Zhonghua Li, Yanchun Liu, Zhi Song, 2018, Qual. Reliab. Eng. Int..

Using p values to design statistical process control charts

Peihua Qiu, Zhonghua Li, Zhaojun Wang, 2013 .

A progressive approach for the detection of the coefficient of variation

Zhonghua Li, Li Jin, Jiujun Zhang, 2021, Qual. Reliab. Eng. Int..

Control chart for monitoring the coefficient of variation with an exponentially weighted moving average procedure

Zhonghua Li, Zhaojun Wang, Zhonghua Li, 2018, Qual. Reliab. Eng. Int..

A new exponentially weighted moving average control chart for monitoring the coefficient of variation

Bin Chen, Zhonghua Li, Zhaojun Wang, 2014, Comput. Ind. Eng..

A Cramér-von Mises test-based distribution-free control chart for joint monitoring of location and scale

Zhonghua Li, Jiujun Zhang, Erjie Li, 2017, Comput. Ind. Eng..

Likelihood ratio test-based chart for monitoring the process variability

Chuan He, Zhonghua Li, Zhaojun Wang, 2017, Commun. Stat. Simul. Comput..

An Adaptive Shiryaev–Roberts Procedure for Signalling Varying Location Shifts

Qin Zhou, Zhonghua Li, Zhaojun Wang, 2016, Commun. Stat. Simul. Comput..

A Distribution-free Multivariate Change-point Model for Statistical Process Control

Zhonghua Li, Maoyuan Zhou, Wei Geng, 2015, Commun. Stat. Simul. Comput..

Control chart based on likelihood ratio for monitoring linear profiles

Zhonghua Li, Zhaojun Wang, Jiujun Zhang, 2009, Comput. Stat. Data Anal..

Self-starting control chart for simultaneously monitoring process mean and variance

Zhonghua Li, Zhaojun Wang, Jiujun Zhang, 2010 .

Statistical Process Control Using a Dynamic Sampling Scheme

Peihua Qiu, Zhonghua Li, P. Qiu, 2014, Technometrics.

Phase II monitoring of generalized linear profiles using weighted likelihood ratio charts

Zhonghua Li, Zhaojun Wang, Dequan Qi, 2016, Comput. Ind. Eng..

One-sided Adaptive Truncated Exponentially Weighted Moving Average X¯ Schemes for Detecting Process Mean Shifts

Jinsheng Sun, P. Castagliola, Zhonghua Li, 2022, Quality Technology & Quantitative Management.

A control scheme for monitoring process covariance matrices with more variables than observations

Fugee Tsung, Zhonghua Li, F. Tsung, 2018, Qual. Reliab. Eng. Int..

A Multivariate Sign Chart for Monitoring Process Shape Parameters

Longcheen Huwang, Changliang Zou, Zhonghua Li, 2013 .

A new adaptive control chart for monitoring process mean and variability

Zhonghua Li, Zhaojun Wang, Jiujun Zhang, 2012 .

Identification of outlying observations for large-dimensional data

Zhonghua Li, Tao Wang, Xiaona Yang, 2021, Journal of applied statistics.

Rank-based EWMA procedure for sequentially detecting changes of process location and variability

Min Xie, Zhonghua Li, Maoyuan Zhou, 2018 .

Weighted likelihood ratio chart for statistical monitoring of queueing systems

Zhonghua Li, Zhaojun Wang, Dequan Qi, 2017 .

Distribution-free monitoring of univariate processes

Peihua Qiu, Zhonghua Li, P. Qiu, 2011 .

A multivariate control chart for simultaneously monitoring process mean and variability

Zhonghua Li, Zhaojun Wang, Jiujun Zhang, 2010, Comput. Stat. Data Anal..

Adaptive CUSUM control chart with variable sampling intervals

Zhonghua Li, Yunzhao Luo, Zhaojun Wang, 2009, Comput. Stat. Data Anal..