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Rate of convergence of empirical measures for exchangeable sequences

  • Patrizia Berti EMAIL logo , Luca Pratelli and Pietro Rigo
Published/Copyright: November 30, 2017
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Abstract

Let S be a finite set, (Xn) an exchangeable sequence of S-valued random variables, and μn = (1/n) i=1nδXi the empirical measure. Then, μn(B)a.s.μ(B) for all BS and some (essentially unique) random probability measure μ. Denote by 𝓛(Z) the probability distribution of any random variable Z. Under some assumptions on 𝓛(μ), it is shown that

anρ[L(μn),L(μ)]bnandρ[L(μn),L(an)]cnu

where ρ is the bounded Lipschitz metric and an(⋅) = P(Xn+1 ∈ ⋅ | X1, …, Xn) is the predictive measure. The constants a, b, c > 0 and u ∈ (12, 1] depend on 𝓛(μ) and card (S) only.


Dedicated to Professor Paolo de Lucia on his 80th birthday

Communicated by Anna De Simone


References

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Received: 2016-4-28
Accepted: 2016-9-26
Published Online: 2017-11-30
Published in Print: 2017-11-27

© 2017 Mathematical Institute Slovak Academy of Sciences

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