| 工作经历 |
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研究领域 |
Generalized likelihood ratio test, high-dimensional data analysis, belief inference, generalized p-value and generalized interval estimation, goodness-of-fit test, multiple hypothesis test, discriminant analysis, allowable and minimal maximality of parameter estimation. |
| 科研成果 |
1. Permissibility of parameter estimation in multivariate statistics (19401020);
2. Inference of faith and its application (10271013);
3. Nonparametric and semiparametric Fiducial inference (10771015);
4. P-value (11071015) of statistical hypothesis testing;
5. Statistical inference based on likelihood function (11471035).
Participated in the National Natural Science Foundation of China
1. Several problems in statistical decision-making and small-sample inference (19871088);
2. Sieve likelihood ratio and small sample conditional inference theory research (10071090);
3. Research on some frontier issues of dimensionality reduction of high-dimensional data (11471030).
Other projects hosted
1. Parameter estimation in linear regression system, Natural Science Foundation of Shandong Province;
2. Conditional Inference in Statistics, National Natural Science Postdoctoral Foundation.
Academic papers
[10] Yuanyuan Jiang and Xingzhong Xu, Testing the skewness of skew-normal distribution by Bayes factors, Journal of Statistical Planning and Inference, 2022, 220: 24-48.
[9] Zhendong Wang and Xingzhong Xu, Testing high dimensional covariance matrices via posterior Bayes factor, Journal of Multivariate Analysis, 2021, 181, Article Number 104674.
[8] Zhendong Wang & Xingzhong Xu, Calibration of posterior predictive p-values for model checking, Journal of Statistical Computation and Simulation, 2021, 91(6):1212-1242.
[7] Zhendong Wang and Xingzhong Xu, High-dimensional sphericity test by extended likelihood ratio, Metrika, 2021, 84:1169-1212.
[6] Yuqi Long and Xingzhong Xu, Bayesian decision rules to classification problems, Australian & New Zealand Journal of Statistics, 2021, 63(2): 394-415.
[5] Wang Rui, Xu, Xingzhong, A Bayesian-motivated test for high-dimensional linear regression models with fixed design matrix, Statistical papers, 2021, 62:1821-1852.
[4] Wang Rui, Xu Xingzhong, Least favorable direction test for multivariate analysis of variance in high dimension. Statistica Sinica, 2021, 31:1-24.
[3] Mingxiang Cao, Peng Sun, Daojiang He, Rui Wang and Xingzhong Xu, A test on linear hypothesis of k-sample means in high-dimensional data, Statistics and Its Interface, 2020, 13:27-36.
[2] Wang Rui, Xu Xingzhong, A feasible high dimensional randomization test for the mean vector, Journal of Statistical Planning and Inference, 2019, 199:160-178.
[1] Wang Rui, Xu Xingzhong, On two-sample mean tests under spiked covariances, Journal of Multivariate Analysis, 2018, 167:225-249. |
科研项目 |
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