Spelling suggestions: "subject:"[een] STOCHASTIC"" "subject:"[enn] STOCHASTIC""
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Biconvex programming and deterministic and stochastic location allocation problemsSelim, Shokri Zaki 12 1900 (has links)
No description available.
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Global optimization of stochastic functionsAl-Mharmah, Hisham 12 1900 (has links)
No description available.
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Stochastic behavior of resonant, nearly-linear oscillator systems for arbitrarily small nonlinear couplingLunsford, Gary Hamilton 12 1900 (has links)
No description available.
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Some topics in risk-sensitive stochastic dynamic modelsChung, Kun-Jen 08 1900 (has links)
No description available.
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Brownian approximations for queueing networks with finite buffers : modeling, heavy traffic analysis and numerical implementationsDai, Wanyang 12 1900 (has links)
No description available.
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Higher order algorithms for the numerical integration of stochastic differential equationsHoneycutt, Rebecca Lee 08 1900 (has links)
No description available.
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Random evolutions with feedbackSiegrist, Kyle Travis 05 1900 (has links)
No description available.
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Probabilistic and Stochastic Computational Models: from Nanoelectronic to Biological ApplicationsLiang, Jinghang Unknown Date
No description available.
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Multichannel autoregressive data modelling in geophysicsTyraskis, Panagiotis A. January 1979 (has links)
No description available.
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General tightness conditions and weak convergence of point processesSchiopu-Kratina, I. (Ioana) January 1985 (has links)
In this dissertation, we consider two aspects of the theory of weak convergence of cadlag processes. / We first give a necessary and sufficient condition for the tightness of a sequence of cadlag processes (chapters 2,3) which generalizes Rebolledo's condition (see 13 ). It is a stochastic condition in the sense that stopping times rather than deterministic times are used in the statement. / We then discuss the predictability of the limit of a sequence of predictable processes (chapters 4-6). For a convergent sequence of point processes we show that, if the sequence of compensators converges, then the limit of compensators is the compensator of the limit of point processes (chapters 4,5). / Finally, we prove in Chapter 6 that extended weak convergence of a sequence of increasing predictable processes ensures the predictability of the limit.
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