焦虑
发表于 2025-3-25 06:59:10
R. S. Liptser,A. N. Shiryayev of theoretical perspectives in the humanities.They also articulate conceptions of philosophy of medicine andbioethics from various practice experiences, and bring criticalattention to aspects of the contemporary health policy.978-90-481-4569-0978-0-306-48133-8
辫子带来帮助
发表于 2025-3-25 09:03:29
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ADORE
发表于 2025-3-25 13:17:35
Conditionally Gaussian processes,Let (.), = (....), 0 ≤. ≤ ., be a random process with unobservable first component and observable second component.
植物茂盛
发表于 2025-3-25 18:24:05
Optimal nonlinear filtering: interpolation and extrapolation of components of conditionally GaussiaLet (.), = (....) 0 ≤. ≤ ., be a continuous random diffusion type process with ., ..
exacerbate
发表于 2025-3-25 20:45:05
Conditionally Gaussian sequences: filtering and related problems,The two previous chapters dealt with problems of filtering, interpolation and extrapolation for the conditionally Gaussian random processes (.), in continuous time . ≥ O. In the present chapter these problems will be investigated for random sequences with discrete time . = 0, Δ, 2Δ,. . ., having the property of “conditional Gaussianness” as well.
FEAT
发表于 2025-3-26 04:00:40
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宠爱
发表于 2025-3-26 07:20:14
Parameter estimation and testing of statistical hypotheses for diffusion type processes,Let ξ = (ξ.), 0 ≤ . ≤ ., be a random process with., where . = (..,..., ..) is a vector column of the unknown parameters, -∞ < .. < ∞, . = 1,..., ., and .. = (.;.(.),..., .;.. is the known vector function with the measurable deterministic components .;.(.), . = 1,..., ..
Bureaucracy
发表于 2025-3-26 10:55:36
The structure of local martingales, absolute continuity of measures for point processes, and filterWe established in Theorem 5.7 that any martingale (or local martingale) of a Wiener process permitted a representation as a stochastic integral (see (5.42)). We shall show in Theorem 19.1 that a similar result holds also for point processes.
Eviction
发表于 2025-3-26 13:09:56
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信条
发表于 2025-3-26 18:40:24
https://doi.org/10.1007/978-1-4757-4293-0Applications; Filter; statistics; stochastic process; stochastic processes; stochastischer Prozess