Raquel Prado

34 papers receiving 529 citations

Peers

Raquel Prado
Comparison fields: 5 of 113
  • Statistics and Probability 110
  • Computational Mathematics 7
  • Signal Processing 104
  • Finance 70
  • General Economics, Econometrics and Finance 43
Replace M. M. Gabr with:
M. M. Gabr Egypt
Connor J. Dalzell Canada
Haipeng Shen United States
Granville Tunnicliffe‐Wilson Ghana
Florentina Bunea United States
Diana Mendes Portugal
Hien D. Nguyen Australia
Georgy Shevlyakov Russia
Toby Lewis United States
Raquel Prado relative to M. M. Gabr Egypt M. M. Gabr's profile →
Citations per field
00.5×8.5×
M. M. Gabr · 1×
Citations per year

Countries citing papers authored by Raquel Prado

Since Specialization
Citations

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

Fields of papers citing papers by Raquel Prado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010111
2
Time Series: Modeling, Computation, and Inference
201097
3 199955
4 200129
5 200024
6
Bayesian time-varying autoregressions: Theory, methods and applications
200021
7 200620
8 200817
9 199917
10 202016
11 201616
12 199914
13 201811
14 20139
15 20179
16 20118
17 20218
18 20237
19 20117
20 20187

About Raquel Prado

Raquel Prado is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Signal Processing, Control and Systems Engineering and Statistics and Probability, having authored 37 papers that have together received 549 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (8 papers), Bayesian Methods and Mixture Models (7 papers), Control Systems and Identification (5 papers), Blind Source Separation Techniques (5 papers), Statistical Methods and Inference (5 papers), Electroconvulsive Therapy Studies (5 papers), Treatment of Major Depression (4 papers) and Statistical Methods and Bayesian Inference (4 papers). The work is most often cited by research in Statistics and Probability (110 citations), Computational Mathematics (7 citations), Signal Processing (104 citations), Finance (70 citations) and General Economics, Econometrics and Finance (43 citations). Raquel Prado has collaborated with scholars based in United States, Venezuela and Saudi Arabia. Frequent co-authors include Mike West, Mike West, Andrew D. Krystal, Hernando Ombao, Francisco Javier Molina, Athanasios Kottas, Henry Greenside, Stella Huo, Richard D. Weiner and Lelys Bravo de Guenni. Their work appears in journals such as Journal of the American Statistical Association, Computational Statistics & Data Analysis, Journal of Time Series Analysis, Psychometrika and Depression and Anxiety.

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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