Wolfgang Polonik

960 total citations
27 papers, 567 citations indexed

About

Wolfgang Polonik is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Wolfgang Polonik has authored 27 papers receiving a total of 567 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 4 papers in Statistics, Probability and Uncertainty. Recurrent topics in Wolfgang Polonik's work include Statistical Methods and Inference (12 papers), Advanced Statistical Methods and Models (10 papers) and Bayesian Methods and Mixture Models (8 papers). Wolfgang Polonik is often cited by papers focused on Statistical Methods and Inference (12 papers), Advanced Statistical Methods and Models (10 papers) and Bayesian Methods and Mixture Models (8 papers). Wolfgang Polonik collaborates with scholars based in United States, Germany and United Kingdom. Wolfgang Polonik's co-authors include Qiwei Yao, David M. Mason, Enno Mammen, Prabir Burman, Mark Bolda, S. T. Koike, Samuel Njoroge, Seogchan Kang, Gary E. Vallad and Krishna V. Subbarao and has published in prestigious journals such as Journal of the American Statistical Association, Journal of Econometrics and The Annals of Statistics.

In The Last Decade

Wolfgang Polonik

24 papers receiving 529 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wolfgang Polonik United States 15 359 218 71 65 45 27 567
Peide Shi China 11 497 1.4× 145 0.7× 47 0.7× 63 1.0× 96 2.1× 25 690
Yannick Baraud France 10 322 0.9× 128 0.6× 53 0.7× 52 0.8× 49 1.1× 20 408
Benoı̂t Cadre France 13 238 0.7× 165 0.8× 29 0.4× 33 0.5× 31 0.7× 28 507
Oleg Lepski France 13 489 1.4× 187 0.9× 98 1.4× 54 0.8× 84 1.9× 28 696
Yves Romain France 6 259 0.7× 97 0.4× 40 0.6× 27 0.4× 29 0.6× 16 393
Jacques Dauxois France 8 273 0.8× 97 0.4× 53 0.7× 25 0.4× 34 0.8× 14 423
Boris Brodsky Russia 9 226 0.6× 162 0.7× 58 0.8× 165 2.5× 89 2.0× 30 659
Mark G. Low United States 14 581 1.6× 187 0.9× 113 1.6× 96 1.5× 100 2.2× 29 812
Céline Lévy‐Leduc France 13 267 0.7× 99 0.5× 121 1.7× 50 0.8× 78 1.7× 41 656
Miao Bai-qi China 12 282 0.8× 109 0.5× 122 1.7× 29 0.4× 32 0.7× 47 514

Countries citing papers authored by Wolfgang Polonik

Since Specialization
Citations

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

Fields of papers citing papers by Wolfgang Polonik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wolfgang Polonik

This figure shows the co-authorship network connecting the top 25 collaborators of Wolfgang Polonik. A scholar is included among the top collaborators of Wolfgang Polonik 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 Wolfgang Polonik. Wolfgang Polonik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Balasubramanian, Krishnakumar, et al.. (2024). A flexible approach for normal approximation of geometric and topological statistics. Bernoulli. 30(4). 1 indexed citations
2.
Polonik, Wolfgang, et al.. (2019). Nonparametric confidence regions for level sets: Statistical properties and geometry. Electronic Journal of Statistics. 13(1). 12 indexed citations
3.
Polonik, Wolfgang & Qiwei Yao. (2016). Asymptotics of set-indexed conditional empirical processes based on dependent data. heiDOK (Heidelberg University).
4.
Polonik, Wolfgang, et al.. (2016). Residual Empirical Processes and Weighted Sums for Time‐Varying Processes with Applications to Testing for Homoscedasticity. Journal of Time Series Analysis. 38(1). 72–98. 1 indexed citations
5.
Polonik, Wolfgang, et al.. (2016). Theoretical analysis of nonparametric filament estimation. The Annals of Statistics. 44(3). 15 indexed citations
6.
Mammen, Enno & Wolfgang Polonik. (2013). Confidence regions for level sets. Journal of Multivariate Analysis. 122. 202–214. 29 indexed citations
7.
Polonik, Wolfgang, et al.. (2012). Mode Identification of Volatility in Time-Varying Autoregression. Journal of the American Statistical Association. 107(499). 1217–1229. 6 indexed citations
8.
Njoroge, Samuel, Gary E. Vallad, Seogchan Kang, et al.. (2011). Phenological and Phytochemical Changes Correlate with Differential Interactions ofVerticillium dahliaewith Broccoli and Cauliflower. Phytopathology. 101(5). 523–534. 28 indexed citations
9.
Mason, David M. & Wolfgang Polonik. (2009). Asymptotic normality of plug-in level set estimates. The Annals of Applied Probability. 19(3). 51 indexed citations
10.
Polonik, Wolfgang, et al.. (2009). PRIM analysis. Journal of Multivariate Analysis. 101(3). 525–540. 18 indexed citations
11.
Burman, Prabir & Wolfgang Polonik. (2008). Multivariate mode hunting: Data analytic tools with measures of significance. Journal of Multivariate Analysis. 100(6). 1198–1218. 22 indexed citations
12.
Polonik, Wolfgang & Qiwei Yao. (2008). Testing for multivariate volatility functions using minimum volume sets and inverse regression. Journal of Econometrics. 147(1). 151–162. 4 indexed citations
13.
Polonik, Wolfgang, et al.. (2006). Discrimination of Locally Stationary Time Series Based on the Excess Mass Functional. Journal of the American Statistical Association. 101(473). 240–253. 20 indexed citations
14.
Polonik, Wolfgang, et al.. (2004). Estimation of regression contour clusters—an application of the excess mass approach to regression. Journal of Multivariate Analysis. 94(2). 227–249. 15 indexed citations
15.
Polonik, Wolfgang & Qiwei Yao. (2002). Set-Indexed Conditional Empirical and Quantile Processes Based on Dependent Data. Journal of Multivariate Analysis. 80(2). 234–255. 24 indexed citations
16.
Polonik, Wolfgang & Qiwei Yao. (2000). Conditional Minimum Volume Predictive Regions for Stochastic Processes. Journal of the American Statistical Association. 95(450). 509–519. 38 indexed citations
17.
Polonik, Wolfgang. (1999). Concentration and goodness-of-fit in higher dimensions: (asymptotically) distribution-free methods. The Annals of Statistics. 27(4). 19 indexed citations
18.
Polonik, Wolfgang. (1998). The silhouette, concentration functions and ML-density estimation under order restrictions. The Annals of Statistics. 26(5). 16 indexed citations
19.
Polonik, Wolfgang. (1997). Minimum volume sets and generalized quantile processes. Stochastic Processes and their Applications. 69(1). 1–24. 51 indexed citations
20.
Polonik, Wolfgang. (1995). Density Estimation under Qualitative Assumptions in Higher Dimensions. Journal of Multivariate Analysis. 55(1). 61–81. 27 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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