Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences PDF Download
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| Author | : Maksym Luz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 308 |
| Release | : 2019-12-12 |
| Genre | : Mathematics |
| ISBN | : 1786305038 |
Download Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences Book in PDF, ePub and Kindle
Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.
| Author | : Maksym Luz |
| Publisher | : John Wiley & Sons |
| Total Pages | : 314 |
| Release | : 2019-09-20 |
| Genre | : Mathematics |
| ISBN | : 1119663520 |
Download Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences Book in PDF, ePub and Kindle
Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.
| Author | : Maksym Luz |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 381 |
| Release | : 2024-05-20 |
| Genre | : Business & Economics |
| ISBN | : 311132625X |
Download Non-Stationary Stochastic Processes Estimation Book in PDF, ePub and Kindle
The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word. Methods of stochastic processes estimation depend on two main factors. The first factor is construction of a model of the process being investigated. The second factor is the available information about the structure of the process under consideration. In this book, we propose results of the investigation of the problem of mean square optimal estimation (extrapolation, interpolation, and filtering) of linear functionals depending on unobserved values of stochastic sequences and processes with periodically stationary and long memory multiplicative seasonal increments. Formulas for calculating the mean square errors and the spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral structure of the considered sequences and processes are exactly known. In the case where spectral densities of the sequences and processes are not known exactly while some sets of admissible spectral densities are given, we apply the minimax-robust method of estimation.
| Author | : Georg Lindgren |
| Publisher | : CRC Press |
| Total Pages | : 316 |
| Release | : 2013-10-11 |
| Genre | : Mathematics |
| ISBN | : 1466586192 |
Download Stationary Stochastic Processes for Scientists and Engineers Book in PDF, ePub and Kindle
Suitable for a one-semester course, this text teaches students how to use stochastic processes efficiently. Carefully balancing mathematical rigor and ease of exposition, the book provides students with a sufficient understanding of the theory and a practical appreciation of how it is used in real-life situations. Special emphasis is on the interpretation of various statistical models and concepts as well as the types of questions statistical analysis can answer. To enable hands-on practice, MATLAB code is available online.
| Author | : Kaddour Najim |
| Publisher | : Elsevier |
| Total Pages | : 345 |
| Release | : 2004-07-01 |
| Genre | : Mathematics |
| ISBN | : 008051779X |
Download Stochastic Processes Book in PDF, ePub and Kindle
A ‘stochastic’ process is a ‘random’ or ‘conjectural’ process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process – estimation, optimisation and recursive logarithms – in a form accessible to engineers and which can also be applied to Matlab. Amongst the themes covered in the chapters are mathematical expectation arising from increasing information patterns, the estimation of probability distribution, the treatment of distribution of real random phenomena (in engineering, economics, biology and medicine etc), and expectation maximisation. The latter part of the book considers optimization algorithms, which can be used, for example, to help in the better utilization of resources, and stochastic approximation algorithms, which can provide prototype models in many practical applications. * An engineering approach to applied probabilities and statistics * Presents examples related to practical engineering applications, such as reliability, randomness and use of resources* Readers with varying interests and mathematical backgrounds will find this book accessible
| Author | : D N Shanbhag |
| Publisher | : Gulf Professional Publishing |
| Total Pages | : 990 |
| Release | : 2001 |
| Genre | : Mathematics |
| ISBN | : 9780444500144 |
Download Stochastic Processes: Theory and Methods Book in PDF, ePub and Kindle
This volume in the series contains chapters on areas such as pareto processes, branching processes, inference in stochastic processes, Poisson approximation, Levy processes, and iterated random maps and some classes of Markov processes. Other chapters cover random walk and fluctuation theory, a semigroup representation and asymptomatic behavior of certain statistics of the Fisher-Wright-Moran coalescent, continuous-time ARMA processes, record sequence and their applications, stochastic networks with product form equilibrium, and stochastic processes in insurance and finance. Other subjects include renewal theory, stochastic processes in reliability, supports of stochastic processes of multiplicity one, Markov chains, diffusion processes, and Ito's stochastic calculus and its applications. c. Book News Inc.
| Author | : Kenneth S. Miller |
| Publisher | : Addison Wesley Publishing Company |
| Total Pages | : 270 |
| Release | : 1974 |
| Genre | : Mathematics |
| ISBN | : |
Download Complex Stochastic Processes Book in PDF, ePub and Kindle
| Author | : Peter C. B. Phillips |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2012 |
| Genre | : |
| ISBN | : |
Download Series Estimation of Stochastic Processes Book in PDF, ePub and Kindle
This paper overviews recent developments in series estimation of stochastic processes and some of their applications in econometrics. Underlying this approach is the idea that a stochastic process may under certain conditions be represented in terms of a set of orthonormal basis functions, giving a series representation that involves deterministic functions. Several applications of this series approximation method are discussed. The first shows how a continuous function can be approximated by a linear combination of Brownian motions (BMs), which is useful in the study of the spurious regressions. The second application utilizes the series representation of BM to investigate the effect of the presence of deterministic trends in a regression on traditional unit-root tests. The third uses basis functions in the series approximation as instrumental variables (IVs) to perform efficient estimation of the parameters in cointegrated systems. The fourth application proposes alternative estimators of long-run variances in some econometric models with dependent data, thereby providing autocorrelation robust inference methods in these models. We review some work related to these applications and some ongoing research involving series approximation methods.
| Author | : Yuliya Mishura |
| Publisher | : John Wiley & Sons |
| Total Pages | : 406 |
| Release | : 2017-11-29 |
| Genre | : Mathematics |
| ISBN | : 1119476631 |
Download Theory and Statistical Applications of Stochastic Processes Book in PDF, ePub and Kindle
This book is concerned with the theory of stochastic processes and the theoretical aspects of statistics for stochastic processes. It combines classic topics such as construction of stochastic processes, associated filtrations, processes with independent increments, Gaussian processes, martingales, Markov properties, continuity and related properties of trajectories with contemporary subjects: integration with respect to Gaussian processes, Itȏ integration, stochastic analysis, stochastic differential equations, fractional Brownian motion and parameter estimation in diffusion models.
| Author | : Narahari Umanath Prabhu |
| Publisher | : World Scientific |
| Total Pages | : 356 |
| Release | : 2007 |
| Genre | : Mathematics |
| ISBN | : 9812706267 |
Download Stochastic Processes Book in PDF, ePub and Kindle
Most introductory textbooks on stochastic processes which cover standard topics such as Poisson process, Brownian motion, renewal theory and random walks deal inadequately with their applications. Written in a simple and accessible manner, this book addresses that inadequacy and provides guidelines and tools to study the applications. The coverage includes research developments in Markov property, martingales, regenerative phenomena and Tauberian theorems, and covers measure theory at an elementary level.
