This map shows the geographic impact of Igor Vajda'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 Igor Vajda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor Vajda more than expected).
This network shows the impact of papers produced by Igor Vajda. 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 Igor Vajda. The network helps show where Igor Vajda may publish in the future.
Co-authorship network of co-authors of Igor Vajda
This figure shows the co-authorship network connecting the top 25 collaborators of Igor Vajda.
A scholar is included among the top collaborators of Igor Vajda 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 Igor Vajda. Igor Vajda 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.
Pardo, Leandro, et al.. (2012). Robust median estimator for generalized linear models with binary responses. Kybernetika. 48(4). 768–794.2 indexed citations
2.
Vajda, Igor. (2009). ON METRIC DIVERGENCES OF PROBABILITY MEASURES. Kybernetika. 45(6). 885–900.16 indexed citations
3.
Kůs, V., Domingo Morales, & Igor Vajda. (2008). EXTENSIONS OF THE PARAMETRIC FAMILIES OF DIVERGENCES USED IN STATISTICAL INFERENCE. Kybernetika. 44(1). 95–112.8 indexed citations
4.
Vajda, Igor & Jana Zvárová. (2007). On generalized entropies, Bayesian decisions and statistical diversity. Kybernetika. 43(5). 675–696.11 indexed citations
5.
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
6.
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
9.
Vajda, Igor, et al.. (1998). About the maximum information and maximum likelihood principles. Kybernetika. 34(4). 485–494.5 indexed citations
10.
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
11.
Vajda, Igor, et al.. (1994). Statistical analysis and applications of log-optimal investments. Kybernetika. 30(3). 331–342.2 indexed citations
12.
Vajda, Igor, et al.. (1993). Existence, uniqueness and evaluation of log-optimal investment portfolio. Kybernetika. 29(2). 105–120.6 indexed citations
13.
Vajda, Igor. (1990). Generalization of discrimination-rate theorems of Chernoff and Stein. Kybernetika. 26(4). 273–288.1 indexed citations
14.
Vajda, Igor. (1984). Asymptotic efficiency and robustness of D-estimators.. Kybernetika. 20(5). 358–375.1 indexed citations
15.
Vajda, Igor. (1984). Motivation, existence and equivariance of D-estimators. Kybernetika. 20(3). 189–208.1 indexed citations
Vajda, Igor & Karel Eckschlager. (1980). Analysis of a measurement information.. Kybernetika. 16. 120–144.2 indexed citations
18.
Vajda, Igor. (1970). On the Amount of Information Contained in a Sequence of Independent Observations. Kybernetika. 6. 306–324.8 indexed citations
19.
Vajda, Igor. (1968). Axioms for a-entropy of a generalized probability scheme.. Kybernetika. 4. 105–112.22 indexed citations
20.
Vajda, Igor. (1967). On the statistical decision problems with discrete parameter space.. Kybernetika. 3. 110–126.2 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.