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Stochastic Differential Equations and Processes

Stochastic Differential Equations and Processes

 

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Editorial:
Springer Nature B.V.
Año de edición:
2011
Materia
Probabilidad y estadística
ISBN:
9783642223679

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Preface.- 1.H. Schurz: Basic Concepts of Numerical Analysis of Stochastic Differential Equations Explained by Balanced Implicit Theta Methods .- 2.C.A. Tudor: Kernel Density Estimation, Local Time and Chaos Expansion.- 3.W. Jedidi, J. Almhana, V. Choulakian, R. McGorman: General Shot Noise Processes and Functional Convergence to Stable Processes.- 4.C. El-Nouty: The Lower Classes of the Sub-Fractional Brownian Motion.- 5.M. Erraoui and Y. Ouknine: On the Bounded Variation of the Flow of Stochastic Differential Equation.- 6.A. Ayache, Q. Peng: Stochastic Volatility and Multifractional Brownian Motion.- 7.A. Gulisashvili, J. Vives: Two-sided Estimates for Distribution Densities in Models with Jumps.- 8.M. Lefebvre: Maximizing a Function of the Survival Time of a Wiener Process in an Interval.

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