Yang Ning

1.4k total citations
46 papers, 662 citations indexed

About

Yang Ning is a scholar working on Statistics and Probability, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Yang Ning has authored 46 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Statistics and Probability, 13 papers in Artificial Intelligence and 6 papers in Control and Systems Engineering. Recurrent topics in Yang Ning's work include Statistical Methods and Inference (29 papers), Statistical Methods and Bayesian Inference (26 papers) and Bayesian Methods and Mixture Models (9 papers). Yang Ning is often cited by papers focused on Statistical Methods and Inference (29 papers), Statistical Methods and Bayesian Inference (26 papers) and Bayesian Methods and Mixture Models (9 papers). Yang Ning collaborates with scholars based in United States, Canada and China. Yang Ning's co-authors include Han Liu, Yong Chen, Ethan X. Fang, Jianqing Fan, Hui Zou, Rui Duan, Han Liu, Kosuke Imai, Zhigang Wu and Chao Yang and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Biometrika.

In The Last Decade

Yang Ning

46 papers receiving 646 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Yang Ning United States	14	404	164	66	60	52	46	662
Hongjoong Kim South Korea	9	100 0.2×	144 0.9×	32 0.5×	16 0.3×	88 1.7×	36	511
Klaus Frick Germany	8	111 0.3×	44 0.3×	32 0.5×	74 1.2×	38 0.7×	21	321
Heiko Strathmann United Kingdom	9	104 0.3×	276 1.7×	28 0.4×	21 0.3×	78 1.5×	13	533
Gyemin Lee South Korea	10	51 0.1×	326 2.0×	32 0.5×	8 0.1×	40 0.8×	29	551
Wentao Huang Taiwan	12	167 0.4×	43 0.3×	11 0.2×	8 0.1×	75 1.4×	45	402
Jacek Leśkow Poland	15	72 0.2×	99 0.6×	21 0.3×	7 0.1×	170 3.3×	42	501
Erkki P. Liski Finland	13	163 0.4×	26 0.2×	6 0.1×	8 0.1×	22 0.4×	51	408
Leyza Baldo Dorini Brazil	10	15 0.0×	99 0.6×	10 0.2×	34 0.6×	12 0.2×	27	473
Mickaël Binois France	11	35 0.1×	163 1.0×	4 0.1×	12 0.2×	50 1.0×	29	492

Countries citing papers authored by Yang Ning

Since Specialization

Citations

This map shows the geographic impact of Yang Ning's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yang Ning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yang Ning more than expected).

Fields of papers citing papers by Yang Ning

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang Ning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yang Ning. The network helps show where Yang Ning may publish in the future.

Co-authorship network of co-authors of Yang Ning

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Ning. A scholar is included among the top collaborators of Yang Ning based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yang Ning. Yang Ning is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Xiaohan, Jiayi Tong, Sida Peng, Yong Chen, & Yang Ning. (2024). Communication‐Efficient Distributed Estimation of Causal Effects With High‐Dimensional Data. Stat. 13(3). 1 indexed citations

Ning, Yang & Guang Cheng. (2023). Sparse confidence sets for normal mean models. Information and Inference A Journal of the IMA. 12(3). 1193–1247. 1 indexed citations

Ning, Yang & Jingyi Duan. (2023). Discussion of ‘Statistical inference for streamed longitudinal data’. Biometrika. 110(4). 867–869. 3 indexed citations

Feng, Huijie, Jingyi Duan, Yang Ning, & Jiwei Zhao. (2023). Test of Significance for High-Dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference. Journal of the American Statistical Association. 119(546). 1396–1408. 1 indexed citations

Ning, Yang, et al.. (2023). Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal of the American Statistical Association. 119(548). 2748–2759. 2 indexed citations

Feng, Huijie, Yang Ning, & Jiwei Zhao. (2022). Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses. The Annals of Statistics. 50(4). 3 indexed citations

Duan, Rui, Yang Ning, & Yong Chen. (2021). Heterogeneity-aware and communication-efficient distributed statistical inference. Biometrika. 109(1). 67–83. 39 indexed citations

Fang, Ethan X., Yang Ning, & Runze Li. (2020). Test of significance for high-dimensional longitudinal data. The Annals of Statistics. 48(5). 2622–2645. 20 indexed citations

Ning, Yang, et al.. (2020). Optimal Sampling for Generalized Linear Models Under Measurement Constraints. Journal of Computational and Graphical Statistics. 30(1). 106–114. 23 indexed citations

10.

Feng, Huijie & Yang Ning. (2019). High-dimensional Mixed Graphical Model with Ordinal Data: Parameter Estimation and Statistical Inference. International Conference on Artificial Intelligence and Statistics. 654–663. 12 indexed citations

11.

Duan, Rui, Yang Ning, Shuang Wang, et al.. (2019). A fast score test for generalized mixture models. Biometrics. 76(3). 811–820. 5 indexed citations

12.

Duan, Rui, Yang Ning, Mingfu Zhu, et al.. (2019). Global identifiability of latent class models with applications to diagnostic test accuracy studies: A Gröbner basis approach. Biometrics. 76(1). 98–108. 3 indexed citations

13.

Ning, Jing, et al.. (2017). On pseudolikelihood inference for semiparametric models with boundary problems. Biometrika. 104(1). 165–179. 13 indexed citations

14.

Hong, Chuan, Yang Ning, Shuang Wang, et al.. (2017). PLEMT: A Novel Pseudolikelihood-Based EM Test for Homogeneity in Generalized Exponential Tilt Mixture Models. Journal of the American Statistical Association. 112(520). 1393–1404. 5 indexed citations

15.

Tan, Kean Ming, Yang Ning, Daniela Witten, & Han Liu. (2016). Replicates in high dimensions, with applications to latent variable graphical models. Biometrika. 103(4). 761–777. 5 indexed citations

16.

Li, Shanshan & Yang Ning. (2015). Estimation of covariate‐specific time‐dependent ROC curves in the presence of missing biomarkers. Biometrics. 71(3). 666–676. 8 indexed citations

17.

Chen, Yong, Chuan Hong, Yang Ning, & Xiao Su. (2015). Meta‐analysis of studies with bivariate binary outcomes: a marginal beta‐binomial model approach. Statistics in Medicine. 35(1). 21–40. 15 indexed citations

18.

Ning, Yang & Han Liu. (2014). SPARC: Optimal Estimation and Asymptotic Inference under Semiparametric Sparsity. arXiv (Cornell University). 1 indexed citations

19.

Ning, Yang & Yong Chen. (2014). A Class of Pseudolikelihood Ratio Tests for Homogeneity in Exponential Tilt Mixture Models. Scandinavian Journal of Statistics. 42(2). 504–517. 5 indexed citations

20.

Ning, Yang, Zhigang Wu, & Chao Yang. (2011). Structural Nonlinear Flutter Characteristics Analysis for an Actuator-fin System with Dynamic Stiffness. Chinese Journal of Aeronautics. 24(5). 590–599. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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