Michael H. Neumann

2.6k total citations
58 papers, 1.5k citations indexed

About

Michael H. Neumann is a scholar working on Statistics and Probability, Finance and Artificial Intelligence. According to data from OpenAlex, Michael H. Neumann has authored 58 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Statistics and Probability, 24 papers in Finance and 17 papers in Artificial Intelligence. Recurrent topics in Michael H. Neumann's work include Statistical Methods and Inference (33 papers), Financial Risk and Volatility Modeling (19 papers) and Bayesian Methods and Mixture Models (11 papers). Michael H. Neumann is often cited by papers focused on Statistical Methods and Inference (33 papers), Financial Risk and Volatility Modeling (19 papers) and Bayesian Methods and Mixture Models (11 papers). Michael H. Neumann collaborates with scholars based in Germany, France and United Kingdom. Michael H. Neumann's co-authors include Rainer von Sachs, Ola Hössjer, George Skiadopoulos, Paul Doukhan, Jens‐Peter Kreiß, Markus Reiß, Jörg Polzehl, Rainer Dahlhaus, J. S. Marron and Iain M. Johnstone and has published in prestigious journals such as IEEE Transactions on Information Theory, Biometrika and Journal of Econometrics.

In The Last Decade

Michael H. Neumann

56 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael H. Neumann Germany 23 784 623 327 254 191 58 1.5k
Elias Masry United States 21 1.0k 1.3× 594 1.0× 289 0.9× 429 1.7× 129 0.7× 64 1.7k
Efstathios Paparoditis Cyprus 22 619 0.8× 551 0.9× 452 1.4× 194 0.8× 58 0.3× 71 1.4k
Denis Bosq France 14 1.4k 1.8× 775 1.2× 411 1.3× 571 2.2× 88 0.5× 63 2.4k
Tailen Hsing United States 22 1.1k 1.4× 1.0k 1.6× 417 1.3× 511 2.0× 67 0.4× 61 2.3k
Bing‐Yi Jing Hong Kong 27 1.2k 1.6× 657 1.1× 338 1.0× 458 1.8× 102 0.5× 102 2.3k
Fabienne Comte France 22 863 1.1× 1.3k 2.1× 751 2.3× 283 1.1× 59 0.3× 96 2.1k
Anton Schίck United States 21 1.7k 2.2× 335 0.5× 189 0.6× 536 2.1× 108 0.6× 100 2.1k
D. S. Poskitt Australia 22 375 0.5× 319 0.5× 354 1.1× 169 0.7× 47 0.2× 67 1.2k
Xiaofeng Shao United States 22 822 1.0× 554 0.9× 393 1.2× 263 1.0× 34 0.2× 68 1.4k
Juan Romo Spain 16 596 0.8× 239 0.4× 188 0.6× 254 1.0× 68 0.4× 58 1.2k

Countries citing papers authored by Michael H. Neumann

Since Specialization
Citations

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

Fields of papers citing papers by Michael H. Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael H. Neumann. 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 Michael H. Neumann. The network helps show where Michael H. Neumann may publish in the future.

Co-authorship network of co-authors of Michael H. Neumann

This figure shows the co-authorship network connecting the top 25 collaborators of Michael H. Neumann. A scholar is included among the top collaborators of Michael H. Neumann 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 Michael H. Neumann. Michael H. Neumann 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.
Neumann, Michael H., et al.. (2024). Mixing properties of non‐stationary multi‐variate count processes. Journal of Time Series Analysis. 46(3). 552–581.
2.
Neumann, Michael H., et al.. (2022). Consistency of a nonparametric least squares estimator in integer-valued GARCH models. Journal of nonparametric statistics. 34(2). 491–519. 2 indexed citations
3.
Neumann, Michael H.. (2021). Bootstrap for integer‐valued GARCH(p, q) processes. Statistica Neerlandica. 75(3). 343–363. 6 indexed citations
4.
Fokianos, Konstantinos, et al.. (2020). On Integrated L 1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations. IEEE Transactions on Information Theory. 66(10). 6389–6402. 6 indexed citations
5.
Neumann, Michael H., et al.. (2013). Dependent wild bootstrap for degenerateU- andV-statistics. Journal of Multivariate Analysis. 117. 257–280. 44 indexed citations
6.
Kapetanios, George, Michael H. Neumann, & George Skiadopoulos. (2013). Jumps in Option Prices and Their Determinants: Real-Time Evidence from the E-Mini S&P 500 Option Market. SSRN Electronic Journal. 2 indexed citations
7.
Neumann, Michael H., et al.. (2012). Degenerate $$U$$ - and $$V$$ -statistics under ergodicity: asymptotics, bootstrap and applications in statistics. Annals of the Institute of Statistical Mathematics. 65(2). 349–386. 39 indexed citations
8.
Neumann, Michael H.. (2011). A central limit theorem for triangular arrays of weakly dependent random variables, with applications in statistics. ESAIM Probability and Statistics. 17. 120–134. 19 indexed citations
9.
Meister, Alexander & Michael H. Neumann. (2010). DECONVOLUTION FROM NON-STANDARD ERROR DENSITIES UNDER REPLICATED MEASUREMENTS. 7 indexed citations
10.
Neumann, Michael H., et al.. (2009). Asset Correlations in Turbulent Markets and their Implications on Asset Management. Asia Pacific Journal of Operational Research. 28(1). 608–616. 4 indexed citations
11.
Neumann, Michael H. & Markus Reiß. (2009). Nonparametric estimation for Lévy processes from low-frequency observations. Bernoulli. 15(1). 67 indexed citations
12.
Doukhan, Paul & Michael H. Neumann. (2006). Probability and moment inequalities for sums of weakly dependent random variables, with applications. Stochastic Processes and their Applications. 117(7). 878–903. 45 indexed citations
13.
Neumann, Michael H.. (2006). Deconvolution from panel data with unknown error distribution. Journal of Multivariate Analysis. 98(10). 1955–1968. 25 indexed citations
14.
Neumann, Michael H., et al.. (2006). An exponential inequality under weak dependence. Bernoulli. 12(2). 28 indexed citations
15.
Kreiß, Jens‐Peter, Enno Mammen, Michael H. Neumann, & Jürgen Franke. (2003). Properties of the Nonparametric Autoregressive Bootstrap. SSRN Electronic Journal. 3 indexed citations
16.
Dahlhaus, Rainer & Michael H. Neumann. (2001). Locally adaptive fitting of semiparametric models to nonstationary time series. Stochastic Processes and their Applications. 91(2). 277–308. 15 indexed citations
17.
Marron, J. S., et al.. (1998). Exact Risk Analysis of Wavelet Regression. Journal of Computational and Graphical Statistics. 7(3). 278–309. 55 indexed citations
18.
Neumann, Michael H. & Ola Hössjer. (1997). On the effect of estimating the error density in nonparametric deconvolution. Journal of nonparametric statistics. 7(4). 307–330. 90 indexed citations
19.
Neumann, Michael H.. (1997). Optimal Change‐point Estimation in Inverse Problems. Scandinavian Journal of Statistics. 24(4). 503–521. 24 indexed citations
20.
Neumann, Michael H.. (1992). Second Order Asymptotic Risks of Smoothed Linear Estimators in Nonparametric Regression Models. Statistics. 23(3). 217–236. 1 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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