Large deviations for random matricial moment problems

F. Gamboa, Jan Nagel, A. Rouault, J. Wagener

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Abstract

We consider the moment space MKn corresponding to p×p complex matrix measures defined on K (K=[0,1] or the unit circle). We endow this set with the uniform law. We are mainly interested in large deviations principles (LDP) when n→∞. First we fix an integer k and study the vector of the first k components of a random element of MKn. We obtain a LDP in the set of k-arrays of p×p matrices. Then we lift a random element of MKn into a random measure and prove a LDP at the level of random measures. We end with a LDP on Cartheodory and Schur random functions. These last functions are well connected to the above random measure. In all these problems, we take advantage of the so-called canonical moments technique by introducing new (matricial) random variables that are independent and have explicit distributions.
Original languageEnglish
JournalJournal of Multivariate Analysis
Volume106
Publication statusPublished - 2012
Externally publishedYes

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    Gamboa, F., Nagel, J., Rouault, A., & Wagener, J. (2012). Large deviations for random matricial moment problems. Journal of Multivariate Analysis, 106.