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Multivariate Laplace's approximation with estimated error and application to limit theorems

机译:多变量Laplace的近似值估计误差和应用来限制定理

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In this paper we obtain an approximation for the multivariate Laplace's integral with a large parameter and estimate error term for two cases, when the maximum of the exponent is in the interior of the domain and on the boundary. We are specifically interested in the situation when the function in the exponent depends on the large parameter. As an application we prove weak law of large numbers and central limit theorem. The second result gives different limiting distributions for two cases mentioned above. When the maximum of the exponent is in the interior of the domain it is Normal distribution and if it is on the boundary, it is Exponential in one direction of integration and Normal in other directions. (C) 2019 Elsevier Inc. All rights reserved.
机译:在本文中,我们通过大参数和估计错误术语获得多变量LAPLACE的积分,并且当指数的最大值在域的内部和边界上时,估计错误术语。 我们对指数中的功能取决于大参数时,我们专门对情况感兴趣。 作为一个应用程序,我们证明了大量和中央极限定理的薄弱规律。 第二个结果给出了上述两个案例的不同限制性分布。 当指数的最大值位于域的内部时,它是正常分布,如果在边界上,则在一个集成方向上是指数的,在另一个方向上是正常的。 (c)2019 Elsevier Inc.保留所有权利。

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