Results 211 to 220 of about 36,639 (264)
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On characterization of distribution by conditional expectation
Communications in Statistics, 1975We show that, under mild conditions on h(1), E(h(X)∣X>y) charactarizes the distribution function of K, and exhibit a method of obtainig the distribution whenever E(h(X)∣X>y) is known, in the continuos and in the discrete case The results of Shenbhag (1970) aad Hamdan (1972) follow immediately.
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IMA Journal of Numerical Analysis, 1985
The author presents a stochastic analysis for condition numbers of square matrices. The expected condition analysis has desirable properties under scaling transformations, which enables the equilibration of a matrix to be carried out. An optimal scaling enables the best conditioned of all the possible equilibrated matrices to be determined.
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The author presents a stochastic analysis for condition numbers of square matrices. The expected condition analysis has desirable properties under scaling transformations, which enables the equilibration of a matrix to be carried out. An optimal scaling enables the best conditioned of all the possible equilibrated matrices to be determined.
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A theorem on conditional expectation
IEEE Transactions on Information Theory, 1970A statistic often encountered in various estimation problems is the conditional ensemble average of the time derivative of a random signal given the signal. It turns out that for a very large class of random signals this statistic is equal to zero. This is a rather surprising result and as far as can be determined has not been precisely stated and ...
James E. Mazo, Jack Salz
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Limits of conditional expectations
IEEE Transactions on Information Theory, 1993Summary: If \((X^ N, Y^ N)\) on a probability space \((\Omega^ N, {\mathcal F}^ N, P^ N)\) converge in distribution to \((X,Y)\) on \((\Omega, {\mathcal F}, P)\), it is not necessarily true that the conditional expectations \(E^{P^ N} \{F(X^ N)\mid Y^ N\}\) converge in distribution to \(E^ P \{F(X)\mid Y\}\), even for bounded, continuous functions \(F\)
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On Characterizations of Conditional Expectation
Canadian Mathematical Bulletin, 1973In the following (Ω, α, μ) is a totally σ-finite measure space except where noted. For a sub-σ-algebra β ⊂ α, the conditional expectation E{f|β} off given β is a function measurable relative to β, such thatIn [5] R.G.Douglas proved, among other things the following, in the finite case:Suppose μ(Ω)=l.
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Physica A: Statistical Mechanics and its Applications, 2001
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Alstrøm, Preben +1 more
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