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edited Dec 13, 2012 at 15:29

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Hello I'm sorry if this question is trivial but I haven't been able to find an answer. I'm trying to show that a sequence of distributions on \mathbb{R}^n$\mathbb{R}^n$ converges to the normal distribution by showing that the moments of the distributions converge to those of the normal distribution. Is this sufficient under appropriate assumptions? Thanks

Hello I'm sorry if this question is trivial but I haven't been able to find an answer. I'm trying to show that a sequence of distributions on \mathbb{R}^n converges to the normal distribution by showing that the moments of the distributions converge to those of the normal distribution. Is this sufficient under appropriate assumptions? Thanks

Hello I'm sorry if this question is trivial but I haven't been able to find an answer. I'm trying to show that a sequence of distributions on $\mathbb{R}^n$ converges to the normal distribution by showing that the moments of the distributions converge to those of the normal distribution. Is this sufficient under appropriate assumptions? Thanks

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asked Dec 13, 2012 at 15:10

NA007

When does the limit of moments of multivariate distributions determine the limit distribution?

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