Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences
Download Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences full books in PDF, epub, and Kindle. Read online free Estimation Of Stochastic Processes With Stationary Increments And Cointegrated Sequences ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads.
Author |
: Maksym Luz |
Publisher |
: John Wiley & Sons |
Total Pages |
: 308 |
Release |
: 2019-12-12 |
ISBN-10 |
: 9781786305039 |
ISBN-13 |
: 1786305038 |
Rating |
: 4/5 (39 Downloads) |
Synopsis Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences by : Maksym Luz
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 |
ISBN-10 |
: 9783111326252 |
ISBN-13 |
: 311132625X |
Rating |
: 4/5 (52 Downloads) |
Synopsis Non-Stationary Stochastic Processes Estimation by : Maksym Luz
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 |
: Maksym Luz |
Publisher |
: John Wiley & Sons |
Total Pages |
: 314 |
Release |
: 2019-09-20 |
ISBN-10 |
: 9781119663522 |
ISBN-13 |
: 1119663520 |
Rating |
: 4/5 (22 Downloads) |
Synopsis Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences by : Maksym Luz
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 |
: North-Holland Publishing Company |
Publisher |
: |
Total Pages |
: 1124 |
Release |
: 1999 |
ISBN-10 |
: 03783758 |
ISBN-13 |
: |
Rating |
: 4/5 (58 Downloads) |
Synopsis Journal of Statistical Planning and Inference by : North-Holland Publishing Company
Author |
: American Mathematical Society |
Publisher |
: |
Total Pages |
: 576 |
Release |
: 1987 |
ISBN-10 |
: UOM:39015085209024 |
ISBN-13 |
: |
Rating |
: 4/5 (24 Downloads) |
Synopsis Abstracts of Papers Presented to the American Mathematical Society by : American Mathematical Society
Author |
: Maksym Luz |
Publisher |
: Walter de Gruyter GmbH & Co KG |
Total Pages |
: 310 |
Release |
: 2024-05-20 |
ISBN-10 |
: 9783111325620 |
ISBN-13 |
: 3111325628 |
Rating |
: 4/5 (20 Downloads) |
Synopsis Non-Stationary Stochastic Processes Estimation by : Maksym Luz
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 |
: |
Publisher |
: |
Total Pages |
: 948 |
Release |
: 1999 |
ISBN-10 |
: UOM:39015053598119 |
ISBN-13 |
: |
Rating |
: 4/5 (19 Downloads) |
Synopsis Current Index to Statistics, Applications, Methods and Theory by :
The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Author |
: G. S. Maddala |
Publisher |
: Cambridge University Press |
Total Pages |
: 528 |
Release |
: 1998 |
ISBN-10 |
: 0521587824 |
ISBN-13 |
: 9780521587822 |
Rating |
: 4/5 (24 Downloads) |
Synopsis Unit Roots, Cointegration, and Structural Change by : G. S. Maddala
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author |
: Bruno Sericola |
Publisher |
: John Wiley & Sons |
Total Pages |
: 306 |
Release |
: 2013-08-05 |
ISBN-10 |
: 9781118731536 |
ISBN-13 |
: 1118731530 |
Rating |
: 4/5 (36 Downloads) |
Synopsis Markov Chains by : Bruno Sericola
Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest. The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains. He carefully examines the explosion phenomenon, the Kolmogorov equations, the convergence to equilibrium and the passage time distributions to a state and to a subset of states. These results are applied to birth-and-death processes. He then proposes a detailed study of the uniformization technique by means of Banach algebra. This technique is used for the transient analysis of several queuing systems. Contents 1. Discrete-Time Markov Chains 2. Continuous-Time Markov Chains 3. Birth-and-Death Processes 4. Uniformization 5. Queues About the Authors Bruno Sericola is a Senior Research Scientist at Inria Rennes – Bretagne Atlantique in France. His main research activity is in performance evaluation of computer and communication systems, dependability analysis of fault-tolerant systems and stochastic models.
Author |
: Götz Kersting |
Publisher |
: John Wiley & Sons |
Total Pages |
: 306 |
Release |
: 2017-11-29 |
ISBN-10 |
: 9781786302526 |
ISBN-13 |
: 1786302527 |
Rating |
: 4/5 (26 Downloads) |
Synopsis Discrete Time Branching Processes in Random Environment by : Götz Kersting
Branching processes are stochastic processes which represent the reproduction of particles, such as individuals within a population, and thereby model demographic stochasticity. In branching processes in random environment (BPREs), additional environmental stochasticity is incorporated, meaning that the conditions of reproduction may vary in a random fashion from one generation to the next. This book offers an introduction to the basics of BPREs and then presents the cases of critical and subcritical processes in detail, the latter dividing into weakly, intermediate, and strongly subcritical regimes.