Tim Hesterberg

4.2k citations
30 papers · 2.9k indexed · 2 hit papers · h-index 16

Tim Hesterberg

29 papers receiving 2.8k citations

Hit Papers

Monte Carlo Strategies in Scientific Computing1.1k19902026200220142505007501000

Peers

Tim Hesterberg
Comparison fields: 5 of 198
  • Statistics and Probability 579
  • Management Science and Operations Research 517
  • Statistics, Probability and Uncertainty 265
  • Artificial Intelligence 767
  • Environmental Engineering 229
Replace James E. Gentle with:
James E. Gentle United States
George Casella United States
M. Johnson United States
Alan Julian Izenman United States
Genshiro Kitagawa Japan
Linda Kaufman United States
J. K. Ord United States
G. J. Janacek United Kingdom
Debashis Kushary United States
Yuhong Yang United States
Tim Hesterberg relative to James E. Gentle United States James E. Gentle's profile →
Citations per field
00.5×1.5×2.0×
James E. Gentle · 1×
Citations per year

Countries citing papers authored by Tim Hesterberg

Since Specialization
Citations

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

Fields of papers citing papers by Tim Hesterberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 22 scholars most cited alongside Tim Hesterberg, 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 Tim Hesterberg Line = papers co-authored together Tim Hesterberg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201840
2 2015215
3 2011185
4 201054
5
Least Angle and $L_1$ Regression: A Review
20081
6 200466
7 200329
8
Monte Carlo Strategies in Scientific Computingbreakdown →
20021092
9 200071
10 19971
11 1997101
12 199614
13 19956
14 19953
15 19950
16 19955
17 19936
18 19931
19 19932
20
A regression-based approach to short-term system load forecastingbreakdown →
1990653

About Tim Hesterberg

Tim Hesterberg is a scholar working on Statistics and Probability, Theoretical Computer Science, Statistics, Probability and Uncertainty, Management Science and Operations Research and Marketing, having authored 30 papers that have together received 2.9k indexed citations. Recurring topics across this work include Statistical Methods and Inference (5 papers), Advanced Statistical Methods and Models (5 papers), Bayesian Methods and Mixture Models (3 papers), Probabilistic and Robust Engineering Design (3 papers), Advanced Statistical Process Monitoring (3 papers), Statistical Distribution Estimation and Applications (3 papers), Energy Load and Power Forecasting (2 papers) and Consumer Market Behavior and Pricing (2 papers). The work is most often cited by research in Statistics and Probability (579 citations), Management Science and Operations Research (517 citations), Statistics, Probability and Uncertainty (265 citations), Artificial Intelligence (767 citations) and Environmental Engineering (229 citations). Tim Hesterberg has collaborated with scholars based in United States and Switzerland. Frequent co-authors include A. Papalexopoulos, Phillip I. Good, Dongsheng Tu, Jun Shao, Laura M. Chihara, Dorothy J. Merritts, Chris Fraley, Diane Lambert, Rong Ge and David Chan. Their work appears in journals such as Technometrics, Journal of Computational and Graphical Statistics, Mathematical and Computer Modelling, Statistics and Computing and Journal of the American Statistical Association.

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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