Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
On the self-similar nature of Ethernet traffic (extended version)
19943.7k citationsMurad S. Taqqu, Walter Willinger et al.profile →
Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level
19971.1k citationsWalter Willinger, Murad S. Taqqu et al.profile →
Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance.
19951.0k citationsGennady Samorodnitsky, Murad S. Taqqu et al.profile →
ESTIMATORS FOR LONG-RANGE DEPENDENCE: AN EMPIRICAL STUDY
1995895 citationsMurad S. Taqqu, Vadim Teverovsky et al.profile →
Long-range dependence in variable-bit-rate video traffic
1995858 citationsMurad S. Taqqu, Walter Willinger et al.profile →
Countries citing papers authored by Murad S. Taqqu
Since
Specialization
Citations
This map shows the geographic impact of Murad S. Taqqu'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 Murad S. Taqqu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Murad S. Taqqu more than expected).
This network shows the impact of papers produced by Murad S. Taqqu. 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 Murad S. Taqqu. The network helps show where Murad S. Taqqu may publish in the future.
Co-authorship network of co-authors of Murad S. Taqqu
This figure shows the co-authorship network connecting the top 25 collaborators of Murad S. Taqqu.
A scholar is included among the top collaborators of Murad S. Taqqu 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 Murad S. Taqqu. Murad S. Taqqu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Conti, Pier Luigi, Livia De Giovanni, Stilian Stoev, & Murad S. Taqqu. (2008). Confidence intervals for the long memory parameter based on wavelets and resampling. Statistica Sinica. 18(2). 559–579.8 indexed citations
11.
Bradley, Brendan & Murad S. Taqqu. (2005). How to Estimate Spatial Contagion between Financial Markets. SSRN Electronic Journal.19 indexed citations
12.
Bradley, Brendan & Murad S. Taqqu. (2005). Empirical Evidence on Spatial Contagion Between Financial Markets. SSRN Electronic Journal.22 indexed citations
13.
Bradley, Brendan & Murad S. Taqqu. (2004). Framework for Analyzing Spatial Contagion between Financial Markets. SSRN Electronic Journal.29 indexed citations
Willinger, Walter, Murad S. Taqqu, & Vadim Teverovsky. (1998). Stock Market Prices and Long-Range Dependence. SSRN Electronic Journal.2 indexed citations
16.
Willinger, Walter, Vern Paxson, & Murad S. Taqqu. (1998). Self-similarity and heavy tails: structural modeling of network traffic. 27–53.233 indexed citations
17.
Crovella, Mark, Murad S. Taqqu, & Azer Bestavros. (1998). Heavy-tailed probability distributions in the World Wide Web. 3–25.221 indexed citations
Eberlein, Ernst & Murad S. Taqqu. (1986). Dependence in probability and statistics : a survey of recent results (Oberwolfach, 1985). Birkhäuser eBooks.2 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.