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Lebesgue decomposition of probability measures:Applications to equivalence, singularity and kriging

机译:Lebesgue概率措施的分解:应用于等价,奇点和克里格的应用

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We use Lebesgue decomposition of two probability measures on a measurable space to obtain conditions for their equivalence and singularity in terms of the density of the absolutely continuous part of one probability measure with respect to the other. This allows us to obtain simple proofs of Kakutani’s theorem on product measures (Kakutani, 1948) and an extension of the result of Shepp (1966). In addition, using the density form of two finite-dimensional Gaussian measures, we derive analogues of major results on equivalence and singularity (Parzen, 1963; Kallianpur and Oodaira, 1963; Rozanov, 1968) for Gaussian random fields. These can be used to study the interpolation of the spatial data (Stein, 1999).
机译:我们在可测量的空间上使用两个概率测量的lebesgue分解,以在相对于另一个概率测量的绝对连续部分的密度方面获得其等效和奇点的条件。 这使我们能够获得Kakutani的产品措施的简单证明(Kakutani,1948年)和Shepp(1966)结果的延伸。 此外,使用两种有限维高斯措施的密度形式,我们派生了对等当量和奇点的主要结果(Parzen,1963; Kallianpur和OOdaira,1963; Rozanov,1968)为高斯随机领域。 这些可用于研究空间数据的插值(Stein,1999)。

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