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Titlebook: Gaussian Random Functions; M. A. Lifshits Book 1995 Springer Science+Business Media Dordrecht 1995 Gaussian distribution.Gaussian measure.

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Multi-Dimensional Gaussian Distributions,Distributions in ℝ .. We are now going to extend the notions introduced in Section 1 to the case when ℝ . is replaced by an arbitrary finite-dimensional Euclidean space ℝ..
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Infinite-Dimensional Gaussian Distributions,.. For a numerical random variable ξ defined on a probability space (Ω,.,ℙ), the basic probability characteristics: mean, variance, characteristic function, etc., can be easily calculated given the distribution of this random variable, that is a measure P defined on ℝ. by the formula ..
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The Large Deviations Principle,Let {ξ ., . ∈ .} be a random function whose sample functions are bounded.
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Exact Asymptotics of Large Deviations,Our consideration so far has been restricted to studying the . asymptotics of large deviations. We now focus on the methods which, in some cases, enable to find the . asymptotics.
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Edward Blair,Kathleen Williamson ξ. If . ⊂ ℝ., the term ‘.’ (or simply .) is used instead of the term ‘random function’; if . ⊂ ℝ., . > 1, the expression ‘.’ is used. In these cases, the elements of . are interpreted as the time instants or space points, respectively. If . = ℕ, a random function ξ is called the ..
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https://doi.org/10.1007/978-3-031-05789-2the kernel, some linear subspace .. ⊂ .. Although this kernel has usually measure zero, it is very important for studying various properties of the measure. For instance, having shifted . by an arbitrary vector which belongs to .., we obtain a measure which is absolutely continuous with respect to .
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