Wangxue Chen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Wangxue Chen has a total of 28 co-authors. Here are the top co-authors by number of shared publications:
Rui Yang
Department of Mathematics and Statistics, Jishou University, Jishou, China
6 shared publicationsDongsen Yao
Jishou University
3 shared publicationsXiaofang He
Department of Mathematics and Statistics, Jishou University, Jishou, People's Republic of China
3 shared publications- A. M. Elsawah
Department of Statistics and Data Science, Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist University, Zhuhai, China
2 shared publications Chunxian Long
Jishou University
2 shared publicationsMeng Chen
Department of Mathematics and Statistics, Jishou University, Jishou, China
2 shared publications
Latest Publications
- 7 October 2026
- Published by Taylor & Francis in Statistics
- p. 1-27
Overcoming ranking errors in regression: Fisher information via minimum ranked unequal-size set sampling design
1. Ranked set sampling design (RSSD), introduced by McIntyre [1], revolutionized data collection in settings where precise measurements are costly but ranking is inexpensive. By leveraging auxiliar...
- 7 October 2026
- Published by Taylor & Francis in Statistics
- p. 1-27
Overcoming ranking errors in regression: Fisher information via minimum ranked unequal-size set sampling design
1. Ranked set sampling design (RSSD), introduced by McIntyre [1], revolutionized data collection in settings where precise measurements are costly but ranking is inexpensive. By leveraging auxiliar...
- 14 March 2026
- Published by Elsevier in Journal of Computational and Applied Mathematics
- Vol. 485
Imperfect extreme ranked set sampling design: A framework for robust and efficient inference
- 14 March 2026
- Published by Elsevier in Journal of Computational and Applied Mathematics
- Vol. 485
Imperfect extreme ranked set sampling design: A framework for robust and efficient inference
- 21 February 2026
- Published by Springer Nature in Statistics and Computing
- Vol. 36 (2) , 91
Superior location-scale estimation using moving extreme ranked set sampling design
- 21 February 2026
- Published by Springer Nature in Statistics and Computing
- Vol. 36 (2) , 91
Superior location-scale estimation using moving extreme ranked set sampling design
- 6 October 2025
- Published by Springer Nature in Acta Mathematicae Applicatae Sinica, English Series
- Vol. 41 (4) , 973-984
Exponential-Poisson Parameters Estimation in Moving Extremes Ranked Set Sampling Design
- 6 October 2025
- Published by Springer Nature in Acta Mathematicae Applicatae Sinica, English Series
- Vol. 41 (4) , 973-984
Exponential-Poisson Parameters Estimation in Moving Extremes Ranked Set Sampling Design
- 25 April 2025
- Published by Springer Nature in Statistical Papers
- Vol. 66 (4) , 1-22
Estimation of the population mean under imperfect simple Z ranked set sampling
- 25 April 2025
- Published by Springer Nature in Statistical Papers
- Vol. 66 (4) , 1-22
Estimation of the population mean under imperfect simple Z ranked set sampling
- 13 January 2024
- Published by Springer Nature in Journal of the Korean Statistical Society
- Vol. 53 (2) , 398-415
Large sample properties of maximum likelihood estimator using moving extremes ranked set sampling
- 13 January 2024
- Published by Springer Nature in Journal of the Korean Statistical Society
- Vol. 53 (2) , 398-415
Large sample properties of maximum likelihood estimator using moving extremes ranked set sampling
- 19 April 2023
- Published by Springer Nature in Acta Mathematicae Applicatae Sinica, English Series
- Vol. 39 (2) , 222-231
Best Linear Unbiased Estimators of Location and Scale Ranked Set Parameters under Moving Extremes Sampling Design
- 19 April 2023
- Published by Springer Nature in Acta Mathematicae Applicatae Sinica, English Series
- Vol. 39 (2) , 222-231
Best Linear Unbiased Estimators of Location and Scale Ranked Set Parameters under Moving Extremes Sampling Design
- 2 March 2023
- Published by Springer Nature in Iranian Journal of Science
- Vol. 47 (2) , 515-529
Sampling Information for Generalized Rayleigh Distribution with Application to Parameter Estimation
- 2 March 2023
- Published by Springer Nature in Iranian Journal of Science
- Vol. 47 (2) , 515-529
Sampling Information for Generalized Rayleigh Distribution with Application to Parameter Estimation
- 25 February 2022
- Published by Taylor & Francis in Communications in Statistics - Simulation and Computation
- Vol. 53 (3) , 1274-1284
Fisher information in ranked set sampling from the simple linear regression model
Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this paper, we obtain explicit expressions for the Fisher information matrix in ranked set sampling (RSS) from the simple linear regression model with replicated observations. It has been shown to be the sum of two matrices, one of which is the Fisher information matrix based on simple random sampling (SRS). The numerical results show that RSS provides more information than SRS when the same sample size is used.
- 25 February 2022
- Published by Taylor & Francis in Communications in Statistics - Simulation and Computation
- Vol. 53 (3) , 1274-1284
Fisher information in ranked set sampling from the simple linear regression model
Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this paper, we obtain explicit expressions for the Fisher information matrix in ranked set sampling (RSS) from the simple linear regression model with replicated observations. It has been shown to be the sum of two matrices, one of which is the Fisher information matrix based on simple random sampling (SRS). The numerical results show that RSS provides more information than SRS when the same sample size is used.
- 27 December 2021
- Published by Taylor & Francis in Mathematical Population Studies
- Vol. 30 (1) , 1-21
Maximum likelihood estimation of the parameters of the inverse Gaussian distribution using maximum rank set sampling with unequal samples
Maximum ranked set sampling with unequal samples is a sampling procedure used to reduce the error of ranking of observations and increase the efficiency of statistical inference. It is used for maximum likelihood estimation of the location and shape parameters of the inverse Gaussian distribution. Its asymptotic efficiency is at least 1.4 times higher than those of estimators based on simple random sampling. It is useful in reliability studies and in Bayesian statistics involving the inverse Gaussian distribution.
- 27 December 2021
- Published by Taylor & Francis in Mathematical Population Studies
- Vol. 30 (1) , 1-21
Maximum likelihood estimation of the parameters of the inverse Gaussian distribution using maximum rank set sampling with unequal samples
Maximum ranked set sampling with unequal samples is a sampling procedure used to reduce the error of ranking of observations and increase the efficiency of statistical inference. It is used for maximum likelihood estimation of the location and shape parameters of the inverse Gaussian distribution. Its asymptotic efficiency is at least 1.4 times higher than those of estimators based on simple random sampling. It is useful in reliability studies and in Bayesian statistics involving the inverse Gaussian distribution.