Let Xn be a sequence of integrable real random variables, adapted to a filtration (Gn). Define Cn = √{(1 / n)∑k=1nXk - E(Xn+1 | Gn)} and Dn = √n{E(Xn+1 | Gn) - Z}, where Z is the almost-sure limit of E(Xn+1 | Gn) (assumed to exist). Conditions for (Cn, Dn) → N(0, U) x N(0, V) stably are given, where U and V are certain random variables. In particular, under such conditions, we obtain √n{(1 / n)∑k=1nX_k - Z} = Cn + Dn → N(0, U + V) stably. This central limit theorem has natural applications to Bayesian statistics and urn problems. The latter are investigated, by paying special attention to multicolor randomly reinforced urns
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Let (Xn) be a sequence of integrable real random variables, adapted to a filtration (Gn). Define: Cn...
Let $(X_n)$ be a sequence of integrable real random variables, adapted to a filtration $(\mathcal{G}...
AbstractAn urn contains balls of d≥2 colors. At each time n≥1, a ball is drawn and then replaced tog...
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We prove a Central Limit Theorem for the sequence of random compositions of a two-color randomly rei...
We prove a Central Limit Theorem for the sequence of random compositions of a two-color randomly rei...
International audienceThe purpose of this work is to establish a central limit theorem that can be a...
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An urn contains black and red balls. Let Zn be the proportion of black balls at time n and 0≤LL, the...
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AbstractWe consider central limit theory for urn models in which balls are not necessarily replaced ...
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