Luis E. Nieto‐Barajas

539 total citations
35 papers, 296 citations indexed

About

Luis E. Nieto‐Barajas is a scholar working on Statistics and Probability, Artificial Intelligence and Finance. According to data from OpenAlex, Luis E. Nieto‐Barajas has authored 35 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 7 papers in Finance. Recurrent topics in Luis E. Nieto‐Barajas's work include Bayesian Methods and Mixture Models (23 papers), Statistical Methods and Inference (21 papers) and Statistical Methods and Bayesian Inference (12 papers). Luis E. Nieto‐Barajas is often cited by papers focused on Bayesian Methods and Mixture Models (23 papers), Statistical Methods and Inference (21 papers) and Statistical Methods and Bayesian Inference (12 papers). Luis E. Nieto‐Barajas collaborates with scholars based in Mexico, United States and United Kingdom. Luis E. Nieto‐Barajas's co-authors include Stephen G. Walker, Igor Prünster, Peter Müller, Fernando A. Quintana, Yuan Ji, Guosheng Yin, Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Rajesh Talluri and Dipankar Bandyopadhyay and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Computational Statistics & Data Analysis.

In The Last Decade

Luis E. Nieto‐Barajas

33 papers receiving 286 citations

Peers

Luis E. Nieto‐Barajas
Comparison fields: 5 of 65
  • Statistics and Probability 186
  • Artificial Intelligence 161
  • Economics and Econometrics 38
  • Molecular Biology 32
  • Finance 32
Alexander R. de Leon Canada
Dario Gasbarra Finland
Klaus J. Utikal United States
Fabrizio Leisen United Kingdom
Maria Kalli United Kingdom
Sabrina Giordano Italy
César Sánchez-Sellero Spain
Minggao Gu United States
David T. Frazier Australia
Hock Peng Chan Singapore
Alexander R. de Leon Canada View profile →
Citations per field, relative to Luis E. Nieto‐Barajas
Luis E. Nieto‐Barajas · 1×
Citations per year, relative to Luis E. Nieto‐Barajas
Luis E. Nieto‐Barajas · 1×

Countries citing papers authored by Luis E. Nieto‐Barajas

Since Specialization
Citations

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

Fields of papers citing papers by Luis E. Nieto‐Barajas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luis E. Nieto‐Barajas. 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 Luis E. Nieto‐Barajas. The network helps show where Luis E. Nieto‐Barajas may publish in the future.

Co-authorship network of co-authors of Luis E. Nieto‐Barajas

This figure shows the co-authorship network connecting the top 25 collaborators of Luis E. Nieto‐Barajas. A scholar is included among the top collaborators of Luis E. Nieto‐Barajas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luis E. Nieto‐Barajas. Luis E. Nieto‐Barajas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 2
5 1
6 1
7 0
8
Modeling with normalized random measure mixture models
4
9 11
10 7
11 10
12 3
13 14
14
A sensitivity analysis for Bayesian nonparametric density estimators
13
15 5
16 12
17 3
18 1
19 7
20 44

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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