Stochastic Theories and Deterministic Differential Equations by John F. Moxnes, Kjell Hausken

“…We discuss the concept of “hydrodynamic” stochastic theory, which is not based on the traditional Markovian concept. …”
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Handy formulas for binomial moments by Maciej Skorski

“…Modern Stochastics: Theory and Applications…”
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Perturbation of an α-stable type stochastic process by a pseudo-gradient by Mykola Boiko, Mykhailo Osypchuk

“…Modern Stochastics: Theory and Applications…”
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First-order planar autoregressive model by Sergiy Shklyar

“…Modern Stochastics: Theory and Applications…”
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Heat equation with a general stochastic measure in a bounded domain by Boris Manikin

“…Modern Stochastics: Theory and Applications…”
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A test on the location of tangency portfolio for small sample size and singular covariance matrix by Svitlana Drin, Stepan Mazur, Stanislas Muhinyuza

“…Modern Stochastics: Theory and Applications…”
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Introducing Randomness into First-Order and Second-Order Deterministic Differential Equations by John F. Moxnes, Kjell Hausken

“…We incorporate randomness into deterministic theories and compare analytically and numerically some well-known stochastic theories: the Liouville process, the Ornstein-Uhlenbeck process, and a process that is Gaussian and exponentially time correlated (Ornstein-Uhlenbeck noise). …”
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A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation by Fuhua Chen, Yunmei Chen, Hemant D. Tagare

“…We proposed a novel framework of multiphase segmentation based on stochastic theory and phase transition theory. Our main contribution lies in the introduction of a constructed function so that its composition with phase function forms membership functions. …”
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