B. Ya. Levit

802 citations
27 papers · 467 · h-index 10

Impact in

Papers in

B. Ya. Levit

21 papers receiving 386 citations

Peers

B. Ya. Levit
Comparison fields: 5 of 64
  • Statistics and Probability 241
  • Applied Mathematics 61
  • Finance 58
  • Numerical Analysis 31
  • Artificial Intelligence 162
Replace Michael Nussbaum with:
Michael Nussbaum Germany
Cristina Butucea France
N. G. Ushakov Russia
R.B. Bapat India
Erik Torgersen Norway
Robert W. Keener United States
Yasuko Chikuse Japan
Karim Lounici France
S. Y. Novak United Kingdom
Jacques Dauxois France
B. Ya. Levit relative to Michael Nussbaum Germany Michael Nussbaum's profile →
Citations per field
00.5×3.7×
Michael Nussbaum · 1×
Citations per year

Countries citing papers authored by B. Ya. Levit

Since Specialization
Citations

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

Fields of papers citing papers by B. Ya. Levit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by B. Ya. Levit. 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 B. Ya. Levit. The network helps show where B. Ya. Levit may publish in the future.

Co-authors

The 4 scholars most cited alongside B. Ya. Levit, 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 B. Ya. Levit Line = papers co-authored together B. Ya. Levit links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995221
2 197768
3 197638
4 198121
5 197921
6 199616
7 199615
8
Adaptive non-parametric estimation of smooth multivariate functions
199913
9 199812
10 19839
11 20036
12 19865
13 19965
14 20133
15 20082
16 20102
17 20022
18 20082
19 20152
20 19832

About B. Ya. Levit

B. Ya. Levit is a scholar working on Statistics and Probability, Numerical Analysis, Management Science and Operations Research, Mathematical Physics and Control and Systems Engineering, having authored 27 papers that have together received 467 indexed citations. Recurring topics across this work include Statistical Methods and Inference (13 papers), Advanced Statistical Methods and Models (10 papers), Mathematical Approximation and Integration (5 papers), Mathematical functions and polynomials (3 papers), Control Systems and Identification (3 papers), Optimal Experimental Design Methods (3 papers), Spectral Theory in Mathematical Physics (2 papers) and Reservoir Engineering and Simulation Methods (2 papers). The work is most often cited by research in Statistics and Probability (241 citations), Applied Mathematics (61 citations), Finance (58 citations), Numerical Analysis (31 citations) and Artificial Intelligence (162 citations). B. Ya. Levit has collaborated with scholars based in Canada, South Korea and Netherlands. Frequent co-authors include Richard D. Gill, A. B. Tsybakov, Oleg Lepski and Joo‐Youn Cho. Their work appears in journals such as Bernoulli, Annals of the Institute of Statistical Mathematics, The Annals of Statistics, Mathematical Methods of Statistics and 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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