Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
On Bayesian Modeling of Fat Tails and Skewness
1998677 citationsCarmen Fernández, Mark F. J. SteelJournal of the American Statistical Associationprofile →
Benchmark priors for Bayesian model averaging
2001675 citationsCarmen Fernández, Eduardo Ley et al.profile →
Model uncertainty in cross‐country growth regressions
2001582 citationsCarmen Fernández, Eduardo Ley et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Carmen Fernández
Since
Specialization
Citations
This map shows the geographic impact of Carmen Fernández'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 Carmen Fernández with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carmen Fernández more than expected).
Fields of papers citing papers by Carmen Fernández
This network shows the impact of papers produced by Carmen Fernández. 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 Carmen Fernández. The network helps show where Carmen Fernández may publish in the future.
Co-authorship network of co-authors of Carmen Fernández
This figure shows the co-authorship network connecting the top 25 collaborators of Carmen Fernández.
A scholar is included among the top collaborators of Carmen Fernández 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 Carmen Fernández. Carmen Fernández is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fernández, Carmen, et al.. (2006). Reações envolvendo íons em solução aquosa: uma abordagem problematizadora para a previsão e equacionamento de alguns tipos de reações inorgânicas. Química Nova na Escola. 14–18.2 indexed citations
Fernández, Carmen, et al.. (2004). Fluorescência e estrutura atômica: experimentos simples para abordar o tema. Química Nova na Escola. 39–42.1 indexed citations
11.
Fernández, Carmen, et al.. (2004). A survey-based assessment of cod in Division 3M. DIGITAL.CSIC (Spanish National Research Council (CSIC)).10 indexed citations
12.
Fernández, Carmen, et al.. (2003). (Ultra) distributions of Lp-growth as Boundary Values of Holomorphic Functions. 97(2). 243.4 indexed citations
Bonet, José, Carmen Fernández, & Reinhold Meise. (2000). CHARACTERIZATION OF THE !-HYPOELLIPTIC CONVOLUTION OPERATORS ON ULTRADISTRIBUTIONS. Annales Academiae Scientiarum Fennicae Mathematica. 25(2). 261–284.10 indexed citations
Fernández, Carmen & Mark F. J. Steel. (1998). On Bayesian Modeling of Fat Tails and Skewness. Journal of the American Statistical Association. 93(441). 359–371.677 indexed citations breakdown →
17.
Fernández, Carmen, Jacek Osiewalski, & Mark F. J. Steel. (1996). On the Use of Panel Data in Bayesian Stochastic Frontier Models. Data Archiving and Networked Services (DANS).1 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.