Dani Gamerman

5.7k citations
71 papers · 3.8k indexed · 2 hit papers · h-index 23

Dani Gamerman

67 papers receiving 3.6k citations

Hit Papers

Markov Chain Monte Carlo73720002026200820174008001.2k

Peers

Dani Gamerman
Comparison fields: 5 of 176
  • Statistics and Probability 1.3k
  • Statistics, Probability and Uncertainty 336
  • Finance 379
  • Management Science and Operations Research 392
  • Environmental Engineering 427
Replace Jennifer A. Hoeting with:
Jennifer A. Hoeting United States
Ludwig Fahrmeir Germany
Jeffrey S. Simonoff United States
Brian D. Marx United States
David S. Stoffer United States
B. W. Silverman United Kingdom
James V. Zidek Canada
Song Xi Chen China
George Casella United States
Genshiro Kitagawa Japan
Dani Gamerman relative to Jennifer A. Hoeting United States Jennifer A. Hoeting's profile →
Citations per field
00.5×1.7×
Jennifer A. Hoeting · 1×
Citations per year

Countries citing papers authored by Dani Gamerman

Since Specialization
Citations

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

Fields of papers citing papers by Dani Gamerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20171
2 201516
3 20130
4 201210
5 200922
6 200934
7 200622
8 200632
9 20062
10 20040
11 2004139
12 20049
13 20035
14 20026
15
Bayesian Analysis of Econometric Time Series Models Using Hybrid Integration Rules
20011
16 20008
17 19999
18
Statistical inference : an integrated approach
1999137
19 1998100
20 198727

About Dani Gamerman

Dani Gamerman is a scholar working on Statistics and Probability, Finance, Management Science and Operations Research, Environmental Engineering and Economics and Econometrics, having authored 71 papers that have together received 3.8k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (16 papers), Spatial and Panel Data Analysis (15 papers), Statistical Methods and Inference (15 papers), Financial Risk and Volatility Modeling (11 papers), Economic and Environmental Valuation (9 papers), Advanced Statistical Methods and Models (9 papers), Statistical Distribution Estimation and Applications (8 papers) and Bayesian Methods and Mixture Models (7 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Statistics, Probability and Uncertainty (336 citations), Finance (379 citations), Management Science and Operations Research (392 citations) and Environmental Engineering (427 citations). Dani Gamerman has collaborated with scholars based in Brazil, United States and United Kingdom. Frequent co-authors include Robert L. Strawderman, Hedibert F. Lopes, Hélio S. Migon, Francisco Louzada, Esther Salazar, Sudipto Banerjee, Alan E. Gelfand, Ajax Reynaldo Bello Moreira, Håvard Rue and Fernando Ferraz do Nascimento. Their work appears in journals such as Computational Statistics & Data Analysis, Environmental and Ecological Statistics, Journal of the Royal Statistical Society Series C (Applied Statistics), Journal of the Operational Research Society and Statistics and Computing.

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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