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.
Preface; 1. The nature of time series and their frequency analysis; 2. Foundations; 3. Analytic properties of Fourier transforms and complex matrices; 4. Stochastic properties of finite Fourier transforms; 5. The estimation of power spectra; 6: Analysis of a linear time invariant relation between a stochastic series and several deterministic series; 7. Estimating the second-order spectra of vector-valued series; 8. Analysis of a linear time invariant relation between two vector-valued stochastic series; 9. Principal components in the frequency domain; 10. The canonical analysis of time series; Proofs of theorems; References; Notation index; Author index; Subject index; Addendum.
Number Of Pages:
- ID: 9780898715019
- Saver Delivery: Yes
- 1st Class Delivery: Yes
- Courier Delivery: Yes
- Store Delivery: Yes
Prices are for internet purchases only. Prices and availability in WHSmith Stores may vary significantly
© Copyright 2013 - 2016 WHSmith and its suppliers.
WHSmith High Street Limited Greenbridge Road, Swindon, Wiltshire, United Kingdom, SN3 3LD, VAT GB238 5548 36