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Author: Raphael Abel KasongaPublisher: National Library of Canada
ISBN:
Category :
Languages : en
Pages : 190
Book Description
Asymptotic Parameter Estimation Theory for Stochastic Differential Equations [microform]
![Asymptotic Parameter Estimation Theory for Stochastic Differential Equations [microform] PDF](https://books.google.com/books/content/images/frontcover/k7DoPgAACAAJ?fife=w80-h100)
Author: Raphael Abel KasongaPublisher: National Library of Canada
ISBN:
Category :
Languages : en
Pages : 190
Book Description
Parameter Estimation in Stochastic Differential Equations
Author: Jaya P. N. BishwalPublisher: Springer
ISBN: 3540744487
Category : Mathematics
Languages : en
Pages : 271
Book Description
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Asymptotic Parameter Estimation Theory for Stochastic Differential Equations
Author: Raphael Abel KasongaPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 0
Book Description
Asymptotic Methods in the Theory of Stochastic Differential Equations
Author: A. V. SkorokhodPublisher: American Mathematical Soc.
ISBN: 9780821846865
Category : Mathematics
Languages : en
Pages : 339
Book Description
Written by one of the foremost Soviet experts in the field, this book is intended for specialists in the theory of random processes and its applications. The author's 1982 monograph on stochastic differential equations, written with Iosif Ilich Gikhman, did not include a number of topics important to applications. The present work begins to fill this gap by investigating the asymptotic behavior of stochastic differential equations. The main topics are ergodic theory for Markov processes and for solutions of stochastic differential equations, stochastic differential equations containing a small parameter, and stability theory for solutions of systems of stochastic differential equations.
Asymptotic Methods in the Theory of Stochastic Differential Equations
Author: A. V. SkorokhodPublisher: American Mathematical Soc.
ISBN: 9780821898253
Category : Mathematics
Languages : en
Pages : 362
Book Description
Ergodic theorems: General ergodic theorems Densities for transition probabilities and resolvents for Markov solutions of stochastic differential equations Ergodic theorems for one-dimensional stochastic equations Ergodic theorems for solutions of stochastic equations in $R^d$ Asymptotic behavior of systems of stochastic equations containing a small parameter: Equations with a small right-hand side Processes with rapid switching Averaging over variables for systems of stochastic differential equations Stability. Linear systems: Stability of sample paths of homogeneous Markov processes Linear equations in $R^d$ and the stochastic semigroups connected with them. Stability Stability of solutions of stochastic differential equations Linear stochastic equations in Hilbert space. Stochastic semigroups. Stability: Linear equations with bounded coefficients Strong stochastic semigroups with second moments Stability Bibliography
Parameter Estimation in Stochastic Volatility Models
Author: Jaya P. N. BishwalPublisher: Springer Nature
ISBN: 3031038614
Category : Mathematics
Languages : en
Pages : 634
Book Description
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Asymptotic Properties of Parameter Estimation for Differential Equations
Author: Peisi YanOn the Estimation of Stochastic Differential Equations
Author: Riccardo CesariPublisher:
ISBN:
Category : Diffusion processes
Languages : en
Pages : 48
Book Description
Asymptotic Analysis for Functional Stochastic Differential Equations
Author: Jianhai BaoPublisher: Springer
ISBN: 3319469797
Category : Mathematics
Languages : en
Pages : 159
Book Description
This brief treats dynamical systems that involve delays and random disturbances. The study is motivated by a wide variety of systems in real life in which random noise has to be taken into consideration and the effect of delays cannot be ignored. Concentrating on such systems that are described by functional stochastic differential equations, this work focuses on the study of large time behavior, in particular, ergodicity.This brief is written for probabilists, applied mathematicians, engineers, and scientists who need to use delay systems and functional stochastic differential equations in their work. Selected topics from the brief can also be used in a graduate level topics course in probability and stochastic processes.
Asymptotic Methods in the Theory of Stochastic Differential Equations
Author: Anatoliĭ Vladimirovich SkorokhodPublisher: Amer Mathematical Society
ISBN: 9780821845318
Category : Mathematics
Languages : en
Pages : 339
Book Description