TIME SERIES: DATA ANALYSIS AND THEORY (CLASSICS IN APPLIED By David R.

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Condition
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See all condition definitionsopens in a new window or tab
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“Book is in typical used-Good Condition.  Will show signs of wear to cover and/or pages. There may ...
ISBN-10
0898715016
Book Title
Time Series: Data Analysis and Theory (Classics in Applied
ISBN
9780898715019
Category

About this product

Product Identifiers

Publisher
Society for Industrial AND Applied Mathematics
ISBN-10
0898715016
ISBN-13
9780898715019
eBay Product ID (ePID)
1889600

Product Key Features

Number of Pages
560 Pages
Language
English
Publication Name
Time Series : Data Analysis and Theory
Subject
Probability & Statistics / General, Transformations, Probability & Statistics / Time Series
Publication Year
2001
Type
Textbook
Subject Area
Mathematics
Author
David R. Brillinger
Series
Classics in Applied Mathematics Ser.
Format
Trade Paperback

Dimensions

Item Height
1.1 in
Item Weight
25.5 Oz
Item Length
9 in
Item Width
6 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2001-034170
Dewey Edition
20
Reviews
‘Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It covers a broad collection of theorems. The techniques are illustrated by data analyses and are discussed both heuristically and formally to serve both the applied and the theoretical worker.’IEEE Signal Processing Magazine, 'Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It covers a broad collection of theorems. The techniques are illustrated by data analyses and are discussed both heuristically and formally to serve both the applied and the theoretical worker.' IEEE Signal Processing Magazine, 'Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It covers a broad collection of theorems. The techniques are illustrated by data analyses and are discussed both heuristically and formally to serve both the applied and the theoretical worker.'IEEE Signal Processing Magazine
Series Volume Number
Vol. 36
Illustrated
Yes
Dewey Decimal
519.5/5
Table Of Content
Preface to the Classics Edition Preface to the Expanded Edition Preface to the First Edition Chapter 1: The Nature of Time Series and Their Frequency Analysis Chapter 2: Foundations Chapter 3: Analytic Properties of Fourier Transforms and Complex Matrices Chapter 4: Stochastic Properties of Finite Fourier Transforms Chapter 5: The Estimation of Power Spectra Chapter 6: Analysis of a Linear Time Invariant Relation Between a Stochastic Series and Several Deterministic Series Chapter 7: Estimating the Second-Order Spectra of Vector-Valued Series Chapter 8: Analysis of a Linear Time Invariant Relation Between Two Vector-Valued Stochastic Series Chapter 9: Principal Components in the Frequency Domain Chapter 10: The Canonical Analysis of Time Series Proofs of Theorems References Notation Index Author Index Subject Index Addendum: Fourier Analysis of Stationary Processes.
Synopsis
Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It provides a broad collection of theorems, placing the techniques on firm theoretical ground., Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It provides a broad collection of theorems, placing the techniques on firm theoretical ground. The techniques, which are illustrated by data analyses, are discussed in both a heuristic and a formal manner, making the book useful for both the applied and the theoretical worker. An extensive set of original exercises is included. Time Series: Data Analysis and Theory takes the Fourier transform of a stretch of time series data as the basic quantity to work with and shows the power of that approach. It considers second- and higher-order parameters and estimates them equally, thereby handling non-Gaussian series and nonlinear systems directly. The included proofs, which are generally short, are based on cumulants.
LC Classification Number
QA280.B74 2001

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