Lectures on Stochastic Processes
by K. Ito
Publisher: Tata Institute of Fundamental Research 1960
Number of pages: 207
Description:
In this course of lectures the author discusses the elementary parts of Stochastic Processes from the view point of Markov Processes. Topics covered: Markov Processes; Srong Markov Processes; Multi-dimensional Brownian Motion; Additive Processes; Stochastic Differential Equations; Linear Diffusion.
Download or read it online for free here:
Download link
(multiple formats)
Similar books
Reversibility and Stochastic Networks
by F.P. Kelly - John Wiley and Sons Ltd
The book on vector stochastic processes in equilibrium or stochastic networks, with wide range of applications. It covers the concept of reversibility, the output from a queue, and the epolymerization process quilibrium distribution.
(17326 views)
by F.P. Kelly - John Wiley and Sons Ltd
The book on vector stochastic processes in equilibrium or stochastic networks, with wide range of applications. It covers the concept of reversibility, the output from a queue, and the epolymerization process quilibrium distribution.
(17326 views)
Markov Chains and Stochastic Stability
by S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(22378 views)
by S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(22378 views)
Stochastic Analysis - Notes
by I. F. Wilde
A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.
(15354 views)
by I. F. Wilde
A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.
(15354 views)
Stochastic Differential Equations: Models and Numerics
by Anders Szepessy, et al. - KTH
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.
(8038 views)
by Anders Szepessy, et al. - KTH
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.
(8038 views)