Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences

Product Number: EB00770320
Released: Oct 07, 2019
Business Term: Purchase
ISBN: #9781119663508
Publisher: Wiley-ISTE
Please log in to view pricing

Description

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.

x-large
Genre: Science
Original Publish Date: Sep 25, 2019

Sign up for our email newsletter