This map shows the geographic impact of Leandro Pardo'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 Leandro Pardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leandro Pardo more than expected).
This network shows the impact of papers produced by Leandro Pardo. 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 Leandro Pardo. The network helps show where Leandro Pardo may publish in the future.
Co-authorship network of co-authors of Leandro Pardo
This figure shows the co-authorship network connecting the top 25 collaborators of Leandro Pardo.
A scholar is included among the top collaborators of Leandro Pardo 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 Leandro Pardo. Leandro Pardo is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ghosh, Abhik, et al.. (2020). Robust semiparametric inference for polytomous logistic
\nregression with complex survey design. Library Open Repository (Universidad Complutense Madrid).6 indexed citations
4.
Pardo, Leandro, et al.. (2016). Evolución de la diversidad productiva en Argentina: análisis comparativo a nivel de áreas económicas locales entre 1996 y 2015. NulanFCEyS (Economic and Social National University of Mar del Plata).2 indexed citations
5.
Pardo, Leandro & J. M. Angulo. (2013). 2013: The International Year of Statistics. 29(3). 149–153.1 indexed citations
6.
Pardo, Leandro, et al.. (2012). Robust median estimator for generalized linear models with binary responses. Kybernetika. 48(4). 768–794.2 indexed citations
Nguyen, Truc, et al.. (2007). On Christensen's conjecture. Statistical Papers. 48(3). 523–523.1 indexed citations
9.
Morales, Domingo, Leandro Pardo, & Igor Vajda. (2005). On the optimal number of classes in the Pearson goodness-of-fit tests. Kybernetika. 41(6). 677–698.1 indexed citations
10.
Pardo, J.A., Leandro Pardo, María del Carmen Pardo, & K. Zografos. (2004). An exploratory canonical analysis approach for multinomial populations based on the phi-divergence measure. Kybernetika. 40(6). 757–776.1 indexed citations
11.
Morales, Domingo, Leandro Pardo, María del Carmen Pardo, & Igor Vajda. (2003). Limit laws for disparities of spacings. Journal of nonparametric statistics. 15(3). 325–342.7 indexed citations
Morales, Domingo, et al.. (1999). INFERENCE ABOUT STATIONARY DISTRIBUTIONS OF MARKOV CHAINS BASED ON DIVERGENCES WITH OBSERVED FREQUENCIES. Kybernetika. 35. 265–280.3 indexed citations
14.
Morales, Domingo, et al.. (1997). Testing in stationary models based on divergences of observed and theoretical frequencies.. Kybernetika. 33(5). 465–475.4 indexed citations
15.
Morales, Domingo, Leandro Pardo, & Igor Vajda. (1996). Divergence between various estimates of quantized information sources.. Kybernetika. 32. 395–407.
16.
Pardo, Leandro, et al.. (1994). Discretization problems on generalized entropies and R-divergences.. Kybernetika. 30. 445–460.16 indexed citations
17.
Pardo, Leandro, et al.. (1992). On M-dimensional unified (r,s)-Jensen difference divergence measures and their applications. Kybernetika. 28(4). 309–324.1 indexed citations
18.
Taneja, Inder J., Leandro Pardo, & Domingo Morales. (1991). Λ-measures of hypoentropy and comparison of experiments: Blackwell and Lehmann approach.. Kybernetika. 27(5). 413–420.4 indexed citations
Pardo, Leandro & Domingo Morales. (1990). An index of diversity in stratified random sampling based on the hypoentropy measure. RACO (Revistes Catalanes amb Accés Obert) (Consorci de Serveis Universitaris de Catalunya). 14(1). 11–25.4 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.