John W. Van Ness

9.4k citations
37 papers · 6.4k indexed · 1 hit paper · h-index 15

Impact in

  • Finance top 0.5%
    • Financial Risk and Volatility Modeling
    • Stochastic processes and financial applications
    • Fractional Differential Equations Solutions

Papers in

John W. Van Ness

36 papers receiving 5.9k citations

Hit Papers

Fractional Brownian Motions, Fractional Noises and Applications 1968 · 5.2k citations
5.2k196820261987200610002.0k3.0k4.0k5.0k

Peers

John W. Van Ness
Comparison fields: 5 of 180
  • Finance 1.7k
  • Modeling and Simulation 625
  • Statistical and Nonlinear Physics 1.1k
  • Economics and Econometrics 2.3k
  • Statistics and Probability 610
Replace Jan Beran with:
Jan Beran Germany
René Carmona United States
Kai Lai Chung United States
Murad S. Taqqu United States
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A. Rényi Hungary
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Citations per field
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Citations per year

Countries citing papers authored by John W. Van Ness

Since Specialization
Citations

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

Fields of papers citing papers by John W. Van Ness

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John W. Van Ness. 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 John W. Van Ness. The network helps show where John W. Van Ness may publish in the future.

Co-authors

The 11 scholars most cited alongside John W. Van Ness, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John W. Van Ness Line = papers co-authored together John W. Van Ness links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2000210
2 19976
3 19969
4 19953
5
On estimating the linear relationships when both variables are subject to errors
19942
6 19942
7 199448
8 199220
9 199122
10 19910
11 198311
12 197653
13 197634
14 19733
15 197314
16 19712
17 19696
18 196729
19 196661
20 1965139

About John W. Van Ness

John W. Van Ness is a scholar working on Statistics and Probability, Signal Processing, Statistics, Probability and Uncertainty, Analytical Chemistry and Artificial Intelligence, having authored 37 papers that have together received 6.4k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (8 papers), Advanced Clustering Algorithms Research (6 papers), Bayesian Methods and Mixture Models (4 papers), Fault Detection and Control Systems (4 papers), Spectroscopy and Chemometric Analyses (4 papers), Data Management and Algorithms (4 papers), Statistical Methods and Inference (3 papers) and Advanced Statistical Process Monitoring (3 papers). The work is most often cited by research in Finance (1.7k citations), Modeling and Simulation (625 citations), Statistical and Nonlinear Physics (1.1k citations), Economics and Econometrics (2.3k citations) and Statistics and Probability (610 citations). John W. Van Ness has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Benoît B. Mandelbrot, Chi-Lun Cheng, J. Gani, Lloyd D. Fisher, M. Rosenblatt, Sudhir Gupta, Emanuel Parzen, William Clinger, Michael Woodroofe and Zhenmin Chen. Their work appears in journals such as Technometrics, Biometrika, Journal of the American Statistical Association, SIAM Review and The Annals of Statistics.

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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