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Vidyadhar Mandrekar

    Weak convergence of stochastic processes
    Stochastic Integration in Banach Spaces
    • Stochastic Integration in Banach Spaces

      Theory and Applications

      • 220bladzijden
      • 8 uur lezen

      Utilizing Poisson random measures, this book presents a novel approach to modeling complex systems influenced by random sources, such as financial interest rates and temperature variations. It explores the solutions of stochastic differential equations, focusing on their long-term behavior and sensitivity to initial conditions. The authors delve into integration theory within Banach spaces, extending beyond the typical Gaussian frameworks. Aimed at graduate students and researchers, it requires a solid understanding of stochastic processes, probability, and functional analysis.

      Stochastic Integration in Banach Spaces
    • The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents: Weak convergence of stochastic processes Weak convergence in metric spaces Weak convergence on C [0, 1] and D [0,∞) Central limit theorem for semi-martingales and applications Central limit theorems for dependent random variables Empirical process Bibliography

      Weak convergence of stochastic processes