Hedibert F. Lopes

4.3k total citations · 1 hit paper
66 papers, 2.6k citations indexed

About

Hedibert F. Lopes is a scholar working on Statistics and Probability, Artificial Intelligence and Finance. According to data from OpenAlex, Hedibert F. Lopes has authored 66 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Statistics and Probability, 23 papers in Artificial Intelligence and 22 papers in Finance. Recurrent topics in Hedibert F. Lopes's work include Financial Risk and Volatility Modeling (21 papers), Bayesian Methods and Mixture Models (19 papers) and Statistical Methods and Inference (19 papers). Hedibert F. Lopes is often cited by papers focused on Financial Risk and Volatility Modeling (21 papers), Bayesian Methods and Mixture Models (19 papers) and Statistical Methods and Inference (19 papers). Hedibert F. Lopes collaborates with scholars based in United States, Brazil and Spain. Hedibert F. Lopes's co-authors include Dani Gamerman, Mike West, Nicholas G. Polson, Esther Salazar, Timothy L. Karr, Carlos M. Carvalho, Manyuan Long, Maria D. Vibranovski, Ruey S. Tsay and Vanja Dukić and has published in prestigious journals such as Journal of the American Statistical Association, American Economic Review and Genetics.

In The Last Decade

Hedibert F. Lopes

63 papers receiving 2.5k citations

Hit Papers

Markov Chain Monte Carlo 2006 2026 2012 2019 2006 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hedibert F. Lopes United States 22 661 568 556 533 270 66 2.6k
Dani Gamerman Brazil 23 1.3k 1.9× 851 1.5× 633 1.1× 379 0.7× 422 1.6× 71 3.8k
Arnoldo Frigessi Norway 30 732 1.1× 501 0.9× 571 1.0× 729 1.4× 608 2.3× 121 4.5k
Walter Zucchini Germany 28 946 1.4× 838 1.5× 299 0.5× 291 0.5× 522 1.9× 54 4.3k
George Casella United States 3 992 1.5× 638 1.1× 328 0.6× 169 0.3× 195 0.7× 4 3.9k
Hannah J. White United Kingdom 23 488 0.7× 538 0.9× 764 1.4× 592 1.1× 190 0.7× 56 3.0k
Jennifer A. Hoeting United States 22 1.1k 1.7× 813 1.4× 698 1.3× 217 0.4× 706 2.6× 54 5.2k
Khosrow Dehnad United States 7 632 1.0× 749 1.3× 543 1.0× 226 0.4× 430 1.6× 12 4.3k
Keith Knight Canada 21 2.1k 3.1× 828 1.5× 495 0.9× 675 1.3× 142 0.5× 37 4.2k
Walter Krämer Germany 22 593 0.9× 215 0.4× 1.2k 2.2× 815 1.5× 542 2.0× 120 4.5k
Gerda Claeskens Belgium 30 2.1k 3.2× 694 1.2× 614 1.1× 322 0.6× 123 0.5× 135 3.7k

Countries citing papers authored by Hedibert F. Lopes

Since Specialization
Citations

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

Fields of papers citing papers by Hedibert F. Lopes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hedibert F. Lopes. 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 Hedibert F. Lopes. The network helps show where Hedibert F. Lopes may publish in the future.

Co-authorship network of co-authors of Hedibert F. Lopes

This figure shows the co-authorship network connecting the top 25 collaborators of Hedibert F. Lopes. A scholar is included among the top collaborators of Hedibert F. Lopes 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 Hedibert F. Lopes. Hedibert F. Lopes 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
1.
Frühwirth‐Schnatter, Sylvia, et al.. (2024). Sparse Bayesian Factor Analysis When the Number of Factors Is Unknown (with Discussion). Bayesian Analysis. 20(1). 9 indexed citations
2.
Lopes, Hedibert F., et al.. (2023). Probabilistic Nearest Neighbors Classification. Entropy. 26(1). 39–39.
3.
Frühwirth‐Schnatter, Sylvia, et al.. (2023). When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures. Econometrics. 11(4). 26–26. 5 indexed citations
4.
Hahn, P. Richard, Jingyu He, & Hedibert F. Lopes. (2018). Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors. Journal of Computational and Graphical Statistics. 28(1). 142–154. 19 indexed citations
5.
Lopes, Hedibert F., et al.. (2017). Sequential Bayesian learning for stochastic volatility with variance‐gamma jumps in returns. Applied Stochastic Models in Business and Industry. 34(4). 460–479. 3 indexed citations
6.
Taddy, Matt, Hedibert F. Lopes, & Matt Gardner. (2016). Semi-parametric inference for the means of heavy-tailed distributions. arXiv (Cornell University). 1 indexed citations
7.
Lopes, Hedibert F. & Nicholas G. Polson. (2015). Particle Learning for Fat-Tailed Distributions. Econometric Reviews. 35(8-10). 1666–1691. 6 indexed citations
8.
Nascimento, Fernando Ferraz do, Dani Gamerman, & Hedibert F. Lopes. (2015). Time-varying extreme pattern with dynamic models. Test. 25(1). 131–149. 16 indexed citations
9.
Heckman, James J., et al.. (2013). Treatment Effects: A Bayesian Perspective. Econometric Reviews. 33(1-4). 36–67. 21 indexed citations
10.
Lopes, Hedibert F. & Nicholas G. Polson. (2013). Bayesian Instrumental Variables: Priors and Likelihoods. Econometric Reviews. 33(1-4). 100–121. 26 indexed citations
11.
Vibranovski, Maria D., Yong E. Zhang, Nicholas W. VanKuren, et al.. (2012). Segmental dataset and whole body expression data do not support the hypothesis that non-random movement is an intrinsic property of Drosophila retrogenes. BMC Evolutionary Biology. 12(1). 169–169. 2 indexed citations
12.
Vibranovski, Maria D., Hedibert F. Lopes, Timothy L. Karr, & Manyuan Long. (2009). Stage-Specific Expression Profiling of Drosophila Spermatogenesis Suggests that Meiotic Sex Chromosome Inactivation Drives Genomic Relocation of Testis-Expressed Genes. PLoS Genetics. 5(11). e1000731–e1000731. 158 indexed citations
13.
Ausín, M. Concepción & Hedibert F. Lopes. (2007). BAYESIAN ESTIMATION OF RUIN PROBABILITIES WITH A HETEROGENEOUS AND HEAVY‐TAILED INSURANCE CLAIM‐SIZE DISTRIBUTION. Australian & New Zealand Journal of Statistics. 49(4). 415–434. 9 indexed citations
14.
Lopes, Hedibert F., et al.. (2007). Factor stochastic volatility with time varying loadings and Markov switching regimes. Journal of Statistical Planning and Inference. 137(10). 3082–3091. 52 indexed citations
15.
Lopes, Hedibert F. & Esther Salazar. (2005). Bayesian Model Uncertainty In Smooth Transition Autoregressions. Journal of Time Series Analysis. 27(1). 99–117. 29 indexed citations
16.
Lopes, Hedibert F., Peter Müller, & Gary L. Rosner. (2003). Bayesian Meta‐analysis for Longitudinal Data Models Using Multivariate Mixture Priors. Biometrics. 59(1). 66–75. 21 indexed citations
17.
Huerta, Gabriel & Hedibert F. Lopes. (2000). Bayesian forecasting and inference in latent structure for the Brazilian Industrial Production Index. Brazilian Review of Econometrics. 20(1). 1–26. 3 indexed citations
18.
Lopes, Hedibert F., Ajax Reynaldo Bello Moreira, & Alexandra M. Schmidt. (1999). Hyperparameter estimation in forecast models. Computational Statistics & Data Analysis. 29(4). 387–410. 14 indexed citations
19.
Lopes, Hedibert F., et al.. (1995). Tendencia estocastica do produto no Brasil: efeitos das flutuacoes da taxa de crescimento da produtividade e da taxa do juro real. 25(2). 249–278.
20.
Migon, Hélio S., et al.. (1993). Efeitos dinâmicos dos choques de oferta e demanda agregadas sobre o nível de atividade econômica do Brasil. Revista Brasileira de Economia. 47(2). 177–204. 4 indexed citations

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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