RT Journal Article
T1 A new approach to analyze the independence of statistical tests of randomness
A1 Almaraz Luengo, Elena Salome
A1 Leiva Cerna, Marcos Brian
A1 García Villalba, Luis Javier
A1 Hernández Castro, Julio
AB One of the fundamental aspects when working with batteries of statistic tests is that they should be as efficient as possible, i.e. that they should check the properties and do so in a reasonable computational time. This assumes that there are no tests that are checking the same properties, i.e. that they are not correlated. One of the most commonly used measures to verify the interrelation between variables is the Pearson’s correlation. In this case, linear dependencies are checked, but it may be interesting to verify other types of non-linear relationships between variables. For this purpose, mutual information has recently been proposed, which measures how much information, on average, one random variable provides to another. In this work we analyze some well-known batteries by using correlation analysis and mutual information approaches.
PB Elsevier
SN 0096-3003
YR 2022
FD 2022-04-02
LK https://hdl.handle.net/20.500.14352/71690
UL https://hdl.handle.net/20.500.14352/71690
LA eng
NO Almaraz Luengo, E. S:, Leiva Cerna, M. B., García Villalba, L. J. & Hernández Castro, J. «A New Approach to Analyze the Independence of Statistical Tests of Randomness». Applied Mathematics and Computation, vol. 426, agosto de 2022, p. 127116. DOI.org (Crossref), https://doi.org/10.1016/j.amc.2022.127116.
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 27 dic 2025