Mario Peruggia

718 citations
36 papers · 511 · h-index 11

Impact in

Papers in

    • Statistical Methods and Bayesian Inference 10
    • Statistical Methods and Inference 8
    • Statistical Distribution Estimation and Applications 3
    • Advanced Statistical Methods and Models 3
    • Markov Chains and Monte Carlo Methods 2
    • Bayesian Methods and Mixture Models 8

Mario Peruggia

34 papers receiving 480 citations

Peers

Mario Peruggia
Comparison fields: 5 of 134
  • Statistics and Probability 80
  • Endocrine and Autonomic Systems 33
  • Statistics, Probability and Uncertainty 35
  • General Decision Sciences 9
  • Management Science and Operations Research 55
Replace Raquel Prado with:
Raquel Prado United States
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A. J. van der Merwe South Africa
Jochen Einbeck United Kingdom
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Mario Peruggia relative to Raquel Prado United States Raquel Prado's profile →
Citations per field
00.5×10×16.5×
Raquel Prado · 1×
Citations per year

Countries citing papers authored by Mario Peruggia

Since Specialization
Citations

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

Fields of papers citing papers by Mario Peruggia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data
2003143
2
Total Least Squares and Errors-in-Variables Modeling: Analysis, Algorithms and Applications
200372
3 200633
4 199431
5 199726
6 201026
7 200724
8 200023
9 199321
10 200013
11 199410
12 201610
13 20169
14 20227
15 20017
16 19977
17 20136
18 20006
19 19965
20 20064

About Mario Peruggia

Mario Peruggia is a scholar working on Statistics and Probability, Artificial Intelligence, Cognitive Neuroscience, Experimental and Cognitive Psychology and Management Science and Operations Research, having authored 36 papers that have together received 511 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (10 papers), Statistical Methods and Inference (8 papers), Bayesian Methods and Mixture Models (8 papers), Neural and Behavioral Psychology Studies (5 papers), Statistical Distribution Estimation and Applications (3 papers), Optimal Experimental Design Methods (3 papers), Advanced Statistical Methods and Models (3 papers) and Markov Chains and Monte Carlo Methods (2 papers). The work is most often cited by research in Statistics and Probability (80 citations), Endocrine and Autonomic Systems (33 citations), Statistics, Probability and Uncertainty (35 citations), General Decision Sciences (9 citations) and Management Science and Operations Research (55 citations). Mario Peruggia has collaborated with scholars based in United States, Switzerland and Nepal. Frequent co-authors include Steven N. MacEachern, Jason C. Hsu, Trisha Van Zandt, Peter F. Craigmile, Jason C. Hsu, Thomas J. Santner, Lynn A. D’Andrea, Jeffrey T. Barth, Michael L. Johnson and Robert H. Diamond. Their work appears in journals such as Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Bayesian Analysis, Journal of Mathematical Psychology and Computational Brain & Behavior.

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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