Time series analysis

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the auth...

Full description

Saved in:
Bibliographic Details
Main Author: Madsen, Henrik 1955- (Author)
Format: Book
Language:English
Published: Boca Raton Chapman & Hall/CRC 2008
Series:Texts in statistical science
Subjects:
Online Access:Click Here to View Status and Holdings.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000n a2200000 a 4501
001 wils-398396
005 2019625131851
020 # # |a 9781420059670  |q hardback 
020 # # |a 142005967X  |q hardback 
040 # # |a DLC  |b eng  |c DLC  |d UiTM  |e rda 
041 0 # |a eng 
090 0 0 |a QA280  |b .M32 2008 
100 1 # |a Madsen, Henrik  |d 1955-  |e author 
245 1 0 |a Time series analysis  |c Henrik Madsen 
264 # 1 |a Boca Raton  |b Chapman & Hall/CRC  |c 2008 
264 # 4 |c ©2008 
300 # # |a 380 pages  |b illustrations  |c 25 cm 
336 # # |a text  |2 rdacontent 
337 # # |a unmediated  |2 rdamedia 
338 # # |a volume  |2 rdacarrier 
490 1 # |a Chapman & Hall/CRC texts in statistical science series 
504 # # |a Includes bibliographical references (page [367]-372) and index 
520 # # |a With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the author presents theorems to highlight the most important results, proofs to clarify some results, and problems to illustrate the use of the results for modeling real-life phenomena. The book first provides the formulas and methods needed to adapt a second-order approach for characterizing random variables as well as introduces regression methods and models, including the general linear model. It subsequently covers linear dynamic deterministic systems, stochastic processes, time domain methods where the autocorrelation function is key to identification, spectral analysis, transfer-function models, and the multivariate linear process. The text also describes state space models and recursive and adaptivemethods. The final chapter examines a host of practical problems, including the predictions of wind power production and the consumption of medicine, a scheduling system for oil delivery, and the adaptive modeling of interest rates. 
650 # 0 |a Time-series analysis 
830 # 1 |a Texts in statistical science 
856 4 0 |z Click Here to View Status and Holdings.  |u https://opac.uitm.edu.my/opac/detailsPage/detailsHome.jsp?tid=398396 
964 # # |c BOK  |d 01 
998 # # |a 00264#1a002.8.2||00264#1b002.8.4||00300##a003.4.1||00300##b003.6.1||00300##c003.5.1||00520##a007.2||00520##b007.2||