J.A. Pardo

814 total citations
48 papers, 466 citations indexed

About

J.A. Pardo is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, J.A. Pardo has authored 48 papers receiving a total of 466 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Statistics and Probability, 14 papers in Artificial Intelligence and 10 papers in Management Science and Operations Research. Recurrent topics in J.A. Pardo's work include Advanced Statistical Methods and Models (34 papers), Statistical Methods and Inference (16 papers) and Multi-Criteria Decision Making (10 papers). J.A. Pardo is often cited by papers focused on Advanced Statistical Methods and Models (34 papers), Statistical Methods and Inference (16 papers) and Multi-Criteria Decision Making (10 papers). J.A. Pardo collaborates with scholars based in Spain, Greece and Brazil. J.A. Pardo's co-authors include Leandro Pardo, María del Carmen Pardo, M. Menéndez, K. Zografos, Teresa Pérez, Inder J. Taneja, María Dolores Esteban, Rosa G. González‐Ramírez, Yolanda Marhuenda García and Domingo Morales and has published in prestigious journals such as Information Sciences, Fuzzy Sets and Systems and Journal of the Franklin Institute.

In The Last Decade

J.A. Pardo

46 papers receiving 452 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.A. Pardo Spain 9 177 148 47 46 38 48 466
Adolfo J. Quiróz Venezuela 11 108 0.6× 151 1.0× 24 0.5× 80 1.7× 39 1.0× 37 435
Yunzhang Zhu United States 10 220 1.2× 174 1.2× 47 1.0× 76 1.7× 75 2.0× 19 492
Arnak S. Dalalyan France 11 321 1.8× 170 1.1× 25 0.5× 46 1.0× 31 0.8× 34 484
Lawrence C. Rafsky United States 6 221 1.2× 232 1.6× 63 1.3× 95 2.1× 48 1.3× 6 599
Kei Takeuchi Japan 12 273 1.5× 104 0.7× 69 1.5× 19 0.4× 14 0.4× 57 535
Anthony Brockwell United States 13 146 0.8× 171 1.2× 38 0.8× 25 0.5× 19 0.5× 37 753
Peter Radchenko United States 11 295 1.7× 131 0.9× 53 1.1× 44 1.0× 40 1.1× 16 484
Matthew A. Nunes United Kingdom 9 160 0.9× 181 1.2× 15 0.3× 44 1.0× 33 0.9× 27 450
Cun-Hui Zhang United States 11 449 2.5× 194 1.3× 67 1.4× 99 2.2× 104 2.7× 16 825

Countries citing papers authored by J.A. Pardo

Since Specialization
Citations

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

Fields of papers citing papers by J.A. Pardo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.A. 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 J.A. Pardo. The network helps show where J.A. Pardo may publish in the future.

Co-authorship network of co-authors of J.A. Pardo

This figure shows the co-authorship network connecting the top 25 collaborators of J.A. Pardo. A scholar is included among the top collaborators of J.A. 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 J.A. Pardo. J.A. Pardo 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.
Camacho‐Vallejo, José‐Fernando, et al.. (2024). The latency location routing problem with split deliveries: mathematical formulation and metaheuristic algorithm. International Transactions in Operational Research. 33(3). 1609–1635.
2.
Pardo, J.A.. (2010). An approach to multiway contingency tables based onϕ-divergence test statistics. Journal of Multivariate Analysis. 101(10). 2305–2319. 2 indexed citations
3.
Pardo, J.A. & María del Carmen Pardo. (2007). A simulation study of a new family of test statistics for the Behrens‐Fisher problem. Kybernetes. 36(5/6). 806–816.
4.
Menéndez, M., J.A. Pardo, Leandro Pardo, & K. Zografos. (2006). Conditional tests of marginal homogeneity based on ϕ-divergence test statistics. Applied Mathematics Letters. 20(1). 7–12. 2 indexed citations
5.
Menéndez, M., J.A. Pardo, Leandro Pardo, & K. Zografos. (2005). On tests of symmetry, marginal homogeneity and quasi-symmetry in two-way contingency tables based on minimum φ-divergence estimator with constraints. Journal of Statistical Computation and Simulation. 75(7). 555–580. 7 indexed citations
6.
Menéndez, M., J.A. Pardo, Leandro Pardo, & K. Zografos. (2005). A preliminary test in classification and probabilities of misclassification. Statistics. 39(3). 183–205. 4 indexed citations
7.
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
8.
Pérez, Teresa & J.A. Pardo. (2004). Minimum Kφ-divergence estimator. Applied Mathematics Letters. 17(4). 367–374. 2 indexed citations
9.
Pérez, Teresa & J.A. Pardo. (2003). Goodness-of-fit tests based on $K_\phi $-divergence. Kybernetika. 39(6). 739–752. 1 indexed citations
10.
Pérez, Teresa & J.A. Pardo. (2002). Asymptotic normality for the Kφ-divergence goodness-of-fit tests. Journal of Computational and Applied Mathematics. 145(2). 301–317. 3 indexed citations
11.
Menéndez, M., J.A. Pardo, & Leandro Pardo. (2001). RAO'S STATISTIC FOR THE ANALYSIS OF UNIFORM ASSOCIATION IN CROSS-CLASSIFICATIONS. Communication in Statistics- Theory and Methods. 30(12). 2655–2681. 2 indexed citations
12.
Pardo, María del Carmen & J.A. Pardo. (2000). Use of Rényi's divergence to test for the equality of the coefficients of variation. Journal of Computational and Applied Mathematics. 116(1). 93–104. 11 indexed citations
13.
Menéndez, M., J.A. Pardo, & María del Carmen Pardo. (1998). Estimators based on sample quantiles using (h, φ)-entropy measures. Applied Mathematics Letters. 11(4). 99–104. 3 indexed citations
14.
Menéndez, M., J.A. Pardo, Leandro Pardo, & María del Carmen Pardo. (1997). The Jensen-Shannon divergence. Journal of the Franklin Institute. 334(2). 307–318. 248 indexed citations
15.
Pardo, J.A., et al.. (1997). A statistical information theory approach to compare the homogeneity of several variances. Computational Statistics & Data Analysis. 24(4). 411–416. 8 indexed citations
16.
Pardo, María del Carmen & J.A. Pardo. (1995). Statistical applications of order $\alpha$-$\beta$ weighted information energy. Applications of Mathematics. 40(4). 305–317. 1 indexed citations
17.
Pardo, María del Carmen & J.A. Pardo. (1994). A test for independence based on the Information Energy. Journal of the Franklin Institute. 331(1). 13–22. 1 indexed citations
18.
Menéndez, M., Inder J. Taneja, & J.A. Pardo. (1993). A fuzzy probabilistic information system comparison criterion: Applications and properties. Fuzzy Sets and Systems. 58(2). 171–183. 1 indexed citations
19.
20.
Pardo, Leandro, M. Menéndez, & J.A. Pardo. (1988). A sequential selection method of a fixed number of fuzzy information systems based on the information energy gain. Fuzzy Sets and Systems. 25(1). 97–105. 11 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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