Lu Lin

706 total citations
55 papers, 505 citations indexed

About

Lu Lin is a scholar working on Statistics and Probability, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Lu Lin has authored 55 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 9 papers in Control and Systems Engineering. Recurrent topics in Lu Lin's work include Statistical Methods and Inference (42 papers), Advanced Statistical Methods and Models (26 papers) and Statistical Methods and Bayesian Inference (19 papers). Lu Lin is often cited by papers focused on Statistical Methods and Inference (42 papers), Advanced Statistical Methods and Models (26 papers) and Statistical Methods and Bayesian Inference (19 papers). Lu Lin collaborates with scholars based in China, United States and Hong Kong. Lu Lin's co-authors include Lixing Zhu, Xia Cui, Gaorong Li, Wensheng Guo, Xiuli Wang, Jun Lü, Peng Zeng, Lili Liu, Ling Jian and Tianyu Wang and has published in prestigious journals such as Advanced Materials, Journal of Business Research and The Annals of Statistics.

In The Last Decade

Lu Lin

51 papers receiving 495 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lu Lin China	13	412	89	67	52	35	55	505
Zhongzhan Zhang China	11	285 0.7×	73 0.8×	57 0.9×	82 1.6×	37 1.1×	61	394
Jelena Bradić United States	8	282 0.7×	86 1.0×	43 0.6×	30 0.6×	18 0.5×	26	373
Mian Huang China	8	244 0.6×	158 1.8×	37 0.6×	24 0.5×	24 0.7×	24	338
Weihua Zhao China	11	331 0.8×	82 0.9×	57 0.9×	38 0.7×	21 0.6×	55	402
Eitan Greenshtein Israel	8	231 0.6×	117 1.3×	27 0.4×	21 0.4×	39 1.1×	26	337
Zhensheng Huang China	11	269 0.7×	57 0.6×	48 0.7×	30 0.6×	20 0.6×	76	385
Haeran Cho United Kingdom	10	196 0.5×	101 1.1×	50 0.7×	92 1.8×	50 1.4×	24	438
Ching‐Kang Ing Taiwan	9	135 0.3×	40 0.4×	31 0.5×	30 0.6×	67 1.9×	26	260
Christophe Crambes France	8	224 0.5×	84 0.9×	50 0.7×	11 0.2×	12 0.3×	15	283
Hongzhi An China	9	154 0.4×	72 0.8×	89 1.3×	65 1.3×	25 0.7×	27	344

Countries citing papers authored by Lu Lin

Since Specialization

Citations

This map shows the geographic impact of Lu Lin'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 Lu Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu Lin more than expected).

Fields of papers citing papers by Lu Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lu Lin. 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 Lu Lin. The network helps show where Lu Lin may publish in the future.

Co-authorship network of co-authors of Lu Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Lu Lin. A scholar is included among the top collaborators of Lu Lin 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 Lu Lin. Lu Lin 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

Ma, Jingchen, Jin hwan Yoon, Lu Lin, et al.. (2024). A quantitative analysis of the improvement provided by comprehensive annotation on CT lesion detection using deep learning. Journal of Applied Clinical Medical Physics. 25(9). e14434–e14434. 1 indexed citations

Harris, Gregory, et al.. (2021). Bringing Clarity to Issues with Adoption of Digital Manufacturing Capabilities: an Analysis of Multiple Independent Studies. Journal of the Knowledge Economy. 13(4). 2868–2889. 7 indexed citations

Lü, Jun, et al.. (2021). Partition-based feature screening for categorical data via RKHS embeddings. Computational Statistics & Data Analysis. 157. 107176–107176. 1 indexed citations

Luo, Dehui, Hong Weng, Xian‐Tao Zeng, et al.. (2020). Optimally estimating the sample mean and standard deviation from the five-number summary. arXiv (Cornell University). 3 indexed citations

Zeng, Peng, et al.. (2020). Degrees of freedom for regularized regression with Huber loss and linear constraints. Statistical Papers. 62(5). 2383–2405. 4 indexed citations

Yu, Ping, et al.. (2019). Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression. Journal of Machine Learning Research. 20(60). 1–49. 8 indexed citations

Liu, Yongxin, Peng Zeng, & Lu Lin. (2019). Generalized ℓ1-penalized quantile regression with linear constraints. Computational Statistics & Data Analysis. 142. 106819–106819. 10 indexed citations

Lin, Lu, et al.. (2018). Conditional SIRS for nonparametric and semiparametric models by marginal empirical likelihood. Statistical Papers. 61(4). 1589–1606. 2 indexed citations

Wang, Xiuli, et al.. (2017). Handling estimating equation with nonignorably missing data based on SIR algorithm. Journal of Computational and Applied Mathematics. 326. 62–70. 3 indexed citations

10.

Jian, Ling, et al.. (2016). Robust exponential squared loss-based variable selection for high-dimensional single-index varying-coefficient model. Journal of Computational and Applied Mathematics. 308. 330–345. 17 indexed citations

11.

Wang, Xiuli, et al.. (2016). Rapid penalized likelihood-based outlier detection via heteroskedasticity test. Journal of Statistical Computation and Simulation. 87(6). 1206–1229. 2 indexed citations

12.

Guo, Xu, et al.. (2015). Heteroscedasticity checks for single index models. Journal of Multivariate Analysis. 136. 41–55. 6 indexed citations

13.

Lin, Lu, et al.. (2015). Inference for biased models: A quasi-instrumental variable approach. Journal of Multivariate Analysis. 145. 22–36. 2 indexed citations

14.

Li, Gaorong, Lu Lin, & Lixing Zhu. (2011). Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters. Journal of Multivariate Analysis. 105(1). 85–111. 49 indexed citations

15.

Lin, Lu, et al.. (2010). Covariate-Adjusted Partially Linear Regression Models. Communication in Statistics- Theory and Methods. 39(6). 1054–1074. 37 indexed citations

16.

Wang, Xiuli, Fang Chen, & Lu Lin. (2010). Empirical Likelihood Inference for the Parameter in Additive Partially Linear EV Models. Communication in Statistics- Theory and Methods. 39(19). 3513–3524. 9 indexed citations

17.

Lin, Lu, et al.. (2010). Consistent inference for biased sub-model of high-dimensional partially linear model. Journal of Statistical Planning and Inference. 141(5). 1888–1898.

18.

Wang, Xiuli, Gaorong Li, & Lu Lin. (2009). Empirical likelihood inference for semi-parametric varying-coefficient partially linear EV models. Metrika. 73(2). 171–185. 30 indexed citations

19.

Wang, Kaiping & Lu Lin. (2008). Semi-Parametric Density Estimation for Time-Series with Multiplicative Adjustment. Communication in Statistics- Theory and Methods. 37(8). 1274–1283. 2 indexed citations

20.

Lin, Lu. (2006). Quasi Bayesian likelihood. Statistical Methodology. 3(4). 444–455. 10 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.

Explore authors with similar magnitude of impact