We consider a sequence of processes X n (t) defined on half-line 0 ≤ t < ∞. We give sufficient conditions for Large Deviation Principle (LDP) to hold in the space of continuous functions with metric ρ κ (f, g) = sup t≥0 |f (t)−g(t)| 1+t 1+κ , κ ≥ 0. LDP is established for Random Walks, Diffusions, and CEV model of ruin, all defined on the half-line. LDP in this space is "more precise" than that with the usual metric of uniform convergence on compacts.
Here we obtain the exact asymptotics for large and moderate deviations, strong law of large numbers and central limit theorem for chains with unbounded variable length memory.
В данной работе исследуются свойства класса платовидных булевых функций, носитель спектра которых задается рекурсивным классом матриц. Для этой последовательности носителей спектра получено точное число функций с таким носителем спектра. Показано также, что множество этих функций являются классом эквивалентности относительно группы сдвигов функций с таким носителем спектра.
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