Galin L. Jones

5.7k citations
58 papers · 3.3k indexed · 1 hit paper · h-index 19

Galin L. Jones

56 papers receiving 3.2k citations

Hit Papers

Handbook of Markov Chain Monte Carlo1.9k201120262016202150010001.5k

Peers

Galin L. Jones
Comparison fields: 5 of 195
  • Statistics and Probability 1.1k
  • Statistics, Probability and Uncertainty 255
  • Artificial Intelligence 933
  • Equine 38
  • Computational Mathematics 10
Replace Charles J. Geyer with:
Charles J. Geyer United States
B. W. Silverman United Kingdom
David A. Harville United States
Guy P. Nason United Kingdom
Arnold Neumaier Austria
Adrienne W. Kemp United Kingdom
H. O. Lancaster Australia
F. H. C. Marriott United Kingdom
S. Kocherlakota Canada
George Casella United States
Galin L. Jones relative to Charles J. Geyer United States Charles J. Geyer's profile →
Citations per field
00.5×1.5×2.1×
Charles J. Geyer · 1×
Citations per year

Countries citing papers authored by Galin L. Jones

Since Specialization
Citations

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

Fields of papers citing papers by Galin L. Jones

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Galin L. Jones. 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 Galin L. Jones. The network helps show where Galin L. Jones may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Galin L. Jones, 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 Galin L. Jones Line = papers co-authored together Galin L. Jones links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20245
2 20242
3 202310
4 20234
5
New visualizations for Monte Carlo simulations
20191
6 20184
7 201721
8 20157
9 201424
10
Variable-at-a-time Implementations of Metropolis-Hastings
20093
11
Component-wise Markov chain Monte Carlo
20094
12 200926
13
Gibbs Sampling for a Bayesian Hierarchical Version of the General Linear Mixed Model
20076
14 20068
15
Ascent-Based Monte Carlo EM
200318
16 200382
17 200246
18 200119
19 200120
20 200117

About Galin L. Jones

Galin L. Jones is a scholar working on Statistics and Probability, Equine and Computational Mathematics, having authored 58 papers that have together received 3.3k indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (26 papers), Statistical Methods and Inference (24 papers), Bayesian Methods and Mixture Models (19 papers), Statistical Methods and Bayesian Inference (9 papers), Veterinary Equine Medical Research (6 papers), Stochastic processes and statistical mechanics (4 papers), Muscle metabolism and nutrition (3 papers) and Liver Disease and Transplantation (3 papers). The work is most often cited by research in Statistics and Probability (1.1k citations), Statistics, Probability and Uncertainty (255 citations) and Artificial Intelligence (933 citations). Galin L. Jones has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Andrew Gelman, Xiao‐Li Meng, Steve Brooks, Brian Caffo, James P. Hobert, James M. Flegal, Ronald C. Neath, Murali Haran, Richard C. Hill and Wolfgang Jank. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Journal of Nutrition.

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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