Mário de Castro

2.4k citations
72 papers · 1.7k indexed · 1 hit paper · h-index 16

Mário de Castro

64 papers receiving 1.6k citations

Hit Papers

A new family of generalized distributions7782010202620152020250500750

Peers

Mário de Castro
Comparison fields: 5 of 120
  • Statistics and Probability 1.4k
  • Statistics, Probability and Uncertainty 590
  • Management Science and Operations Research 233
  • Finance 169
  • Safety, Risk, Reliability and Quality 109
Replace Marcelo Bourguignon with:
Marcelo Bourguignon Brazil
Ibrahim Elbatal Saudi Arabia
Vicente G. Cancho Brazil
Hassan S. Bakouch Egypt
Miroslav M. Ristić Serbia
M. Masoom Ali United States
Zubair Ahmad Pakistan
Pushpa L. Gupta United States
Ayman Alzaatreh United Arab Emirates
Jafar Ahmadi Iran
Mário de Castro relative to Marcelo Bourguignon Brazil Marcelo Bourguignon's profile →
Citations per field
00.5×1.5×2.1×
Marcelo Bourguignon · 1×
Citations per year

Countries citing papers authored by Mário de Castro

Since Specialization
Citations

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

Fields of papers citing papers by Mário de Castro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mário de Castro. 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 Mário de Castro. The network helps show where Mário de Castro may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20231
3 20210
4 20212
5 202112
6 202021
7 20200
8 20173
9 201625
10 20142
11 201160
12 201050
13 201013
14 20105
15 201014
16 200939
17
Untitled. [Letter to the Editor]
20085
18 200822
19 20072
20 20077

About Mário de Castro

Mário de Castro is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 72 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (27 papers), Statistical Distribution Estimation and Applications (26 papers), Statistical Methods and Inference (22 papers), Advanced Statistical Methods and Models (19 papers), Bayesian Methods and Mixture Models (12 papers), Statistical Methods in Clinical Trials (11 papers), Optimal Experimental Design Methods (10 papers) and Advanced Statistical Process Monitoring (4 papers). The work is most often cited by research in Statistics and Probability (1.4k citations), Statistics, Probability and Uncertainty (590 citations) and Management Science and Operations Research (233 citations). Mário de Castro has collaborated with scholars based in Brazil, Chile and United States. Frequent co-authors include Gauss M. Cordeiro, Josemar Rodrigues, Vicente G. Cancho, N. Balakrishnan, Heleno Bolfarine, Manuel Galea, Francisco Louzada, Jorge L. Bazán, Odemir Martinez Bruno and João B. Florindo. Their work appears in journals such as Journal of Statistical Computation and Simulation, Computational Statistics & Data Analysis, Statistical Papers, Chemometrics and Intelligent Laboratory Systems and Biometrics.

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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