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by Y.A. Kutoyants
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Mathematics
  • Author:
    Y.A. Kutoyants
  • ISBN:
    3885382067
  • ISBN13:
    978-3885382065
  • Genre:
  • Publisher:
    Heldermann Verlag (December 1984)
  • Pages:
    214 pages
  • Subcategory:
    Mathematics
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    1370 kb
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Financial processes as processes in nature, are subject to stochastic fluctuations

Financial processes as processes in nature, are subject to stochastic fluctuations. Stochastic differential equations turn out to be an advantageous repre-sentation of such noisy, real-world problems, and together with their identification, they play an important role in the sectors of finance, but also in physics and biotech-nology. These equations, however, are often hard to represent and to resolve.

A. Kutoyants Parameter Estimation for Stochastic Processes.

Vol 35. Ivan Chajda, Jan Paseka Algebraic Approach to Tense Operators. Vol 34. Miroslav Haviar, Michal Ivaska Vertex Labellings of Simple Graphs. Vol 33. Petar Pavesic, Renzo A. Piccinini Fibrations and their Classification. A.

parameters of a stochastic process. framework of estimation for stochastic processes. In Appendix B, a report on the use of the empirical characteristic.

Statistical Inference for Spatial Poisson Processes, volume 134 of Lecture Notes in Statistics.

Heldermann Verlag, Berlin, 1984. Statistical Inference for Spatial Poisson Processes, volume 134 of Lecture Notes in Statistics. Springer-Verlag, New York, 1998.

Browse other questions tagged reference-request or ask your own question.

In particular I'm assuming that both the drift and volatility are constant over time. Browse other questions tagged reference-request or ask your own question.

Semantic Scholar extracted view of "Parameter Estimation for Stochastic Processes" by Y. oceedings{erEF, title {Parameter Estimation for Stochastic Processes}, author {Yu. Kutoyants}, year {1984} }. Yu. Kutoyants.

Semantic Scholar extracted view of "Parameter Estimation for Stochastic Processes" by Yu.

This book deals with a variety of statistical inference problems for stochastic differential equation. .In each chapter the author starts with useful introductory notes clearly describing the specific models and the problems

This book deals with a variety of statistical inference problems for stochastic differential equation.In each chapter the author starts with useful introductory notes clearly describing the specific models and the problems.

In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a family of random variables. Historically, the random variables were associated with or indexed by a set of numbers, usually viewed.

In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a family of random variables

Kutoyants YA. Parameter estimation for stochastic processes Stochastic calculus for fractional Brownian motion and related processes. Lecture Notes in Mathematics, vol. 1929. Berlin: Springer; 2008.

Kutoyants YA. Parameter estimation for stochastic processes. Liptser R, Shiryaev A. Statistics of random processes II: general theory. New York: Springer-Verlag; 2001. Stochastic calculus for fractional Brownian motion and related processes.