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Radon–Nikodým Theorem

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International Encyclopedia of Statistical Science

The theorem is concerned with the existence of density (derivative) of one measure with respect to another. Let \((\Omega,\mathcal{F})\) be a measurable space, i.e., a set Ω together with a σ-algebra \(\mathcal{F}\) of subsets of Ω. Suppose that ν, μ are two σ-finite positive measures on \((\Omega,\mathcal{F})\) such that ν is absolutely continuous (denoted by ν ≪ μ) with respect to μ, i.e., if μ(A) = 0 for some \(A \in \mathcal{F}\) then ν(A) = 0. The Radon–Nikodým theorem states that these exists a μ-integrable function f : Ω + such that

$$\nu (A) ={ \int \nolimits \nolimits }_{A}f(\omega )\mu (d\omega ),\quad A \in \mathcal{F}.$$

Moreover, f is μ-a.e. unique, in the sense that if f′ also satisfies the above then the μ-measure of the points ω such that f(ω)≠f′(ω) equals zero. The function f is called Radon–Nikodým derivative of μ with respect to ν and this is often denoted by

$$f(\omega ) = \frac{d\nu } {d\mu }(\omega ).$$

The standard proof is as follows. First, assume that μ(Ω)...

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References and Further Reading

  • Bell D (1991) Transformations of measures on an infinite-dimensional vector space. Seminar on stochastic processes (Vancouver 1990). Prog Probab 24:15–25

    Google Scholar 

  • Bogachev V (2008) Differentiable measures and the malliavin calculus (in Russian). R & C Dynamics, Moscow

    Google Scholar 

  • Cameron RH, Martin WT (1944) Transformation of Wiener integrals under translations. Ann Math 45:386–396

    MATH  MathSciNet  Google Scholar 

  • Cover TM, Thomas JA (1991) Elements of information theory. Wiley, New York

    MATH  Google Scholar 

  • Daletskii J, Sokhadze G (1988) Absolute continuity of smooth measures (in Russian). Funct Anal Appl 22(2):77–88

    MathSciNet  Google Scholar 

  • Feldman I (1958) Equivalence and perpendicularity of Gaussian processes. Pac J Math 8:699–708

    MATH  Google Scholar 

  • Gikhman I, Skorokhod A (1971–1975) Theory of stochastic processes, vol 1–3. Nauka, Moscow (in Russian)

    Google Scholar 

  • Ibragimov I, Rozanov J (1970) Gaussian random processes (in Russian). Nauka, Moscow

    Google Scholar 

  • Kallenberg O (2002) Foundations of modern probability, 2nd edn. Springer, New York

    MATH  Google Scholar 

  • Kolmogorov A (1933) Grundbegriffe der Wahrscheinlichkeitsrechnung. Julius Springer, Berlin. (English translation by Chelsea, New York, 1956)

    Google Scholar 

  • Konstantopoulos T (2009) Conditional expectation and probability. This encyclopedia

    Google Scholar 

  • Kulik A, Pilipenko A (2000) Nonlinear transformations of smooth measures in infinite-dimensional spaces. Ukran Math J 52(9):1226–1250

    MATH  MathSciNet  Google Scholar 

  • Kullback S, Leibler RA (1951) On information and sufficiency. Ann Math Stat 22:79–86

    MATH  MathSciNet  Google Scholar 

  • Kyprianou AE (2006) Introductory lectures on fluctuations of Lévy processes with applications. Springer, Heidelberg

    MATH  Google Scholar 

  • Liptser R, Shiryaev A (1974) Statistics of random processes (in Russian). Nauka, Moscow

    Google Scholar 

  • Nikodým O (1930) Sur une généralisation des intégrales de M. J Radon Fundamenta Mathematicae 15:131–179

    MATH  Google Scholar 

  • Radon J (1913) Theorie und Anwendungen der absolut additiven Mengenfunktionen. Sitzber, der Math.Naturwiss. Klasse der Kais. Akademie der Wiss. Wien, 112 Bd. Abt II a/2

    Google Scholar 

  • Williams D (1989) Probability with martingales. Cambridge University Press, Cambridge

    Google Scholar 

  • Yadrenko M (1980) Spectral theory of random fields (in Russian). Visha Shkola, Kiev

    Google Scholar 

  • Zerakidze Z (1969) On the equivalence of distributions of Gaussian fields (in Russian). In: Proceedings of the Tbilisi institute of applied mathematics. Tbilisi, vol 2, pp 215–220

    Google Scholar 

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Konstantopoulos, T., Zerakidze, Z., Sokhadze, G. (2011). Radon–Nikodým Theorem. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_468

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