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Time Series Analysis with Long Memory in View by Uwe Hassler: New

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Time Series Analysis with Long Memory in View
Publication Date
2019-02-01
ISBN
9781119470403
Subject Area
Mathematics
Publication Name
Time Series Analysis with Long Memory in View
Publisher
Wiley & Sons, Incorporated, John
Item Length
9.3 in
Subject
Probability & Statistics / General, Probability & Statistics / Time Series
Publication Year
2018
Series
Wiley Series in Probability and Statistics Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
0.8 in
Author
Uwe Hassler
Item Weight
20.8 Oz
Item Width
6.2 in
Number of Pages
288 Pages

About this product

Product Information

Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof Long memory time series are characterized by a strong dependence between distant events.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119470404
ISBN-13
9781119470403
eBay Product ID (ePID)
240485616

Product Key Features

Number of Pages
288 Pages
Language
English
Publication Name
Time Series Analysis with Long Memory in View
Publication Year
2018
Subject
Probability & Statistics / General, Probability & Statistics / Time Series
Type
Textbook
Subject Area
Mathematics
Author
Uwe Hassler
Series
Wiley Series in Probability and Statistics Ser.
Format
Hardcover

Dimensions

Item Height
0.8 in
Item Weight
20.8 Oz
Item Length
9.3 in
Item Width
6.2 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2018-023760
Dewey Edition
23
Series Volume Number
215
Illustrated
Yes
Dewey Decimal
519.55
Lc Classification Number
Qa280.H385 2018
Table of Content
List of Figures xi Preface xiii List of Notation xv Acronyms xvii 1 Introduction 1 1.1 Empirical Examples 1 1.2 Overview 6 2 Stationary Processes 11 2.1 Stochastic Processes 11 2.2 Ergodicity 14 2.3 Memory and Persistence 22 2.4 Technical Appendix: Proofs 25 3 Moving Averages and Linear Processes 27 3.1 Infinite Series and Summability 27 3.2 Wold Decomposition and Invertibility 32 3.3 Persistence versus Memory 37 3.4 Autoregressive Moving Average Processes 47 3.5 Technical Appendix: Proofs 51 4 Frequency Domain Analysis 57 4.1 Decomposition into Cycles 57 4.2 Complex Numbers and Transfer Functions 62 4.3 The Spectrum 63 4.4 Parametric Spectra 68 4.5 (Asymptotic) Properties of the Periodogram 72 4.6 Whittle Estimation 76 4.7 Technical Appendix: Proofs 81 5 Differencing and Integration 89 5.1 Integer Case 89 5.2 Approximating Sequences and Functions 91 5.3 Fractional Case 95 5.4 Technical Appendix: Proofs 99 6 Fractionally Integrated Processes 103 6.1 Definition and Properties 103 6.2 Examples and Discussion 108 6.3 Nonstationarity and Type I Versus II 114 6.4 Practical Issues 118 6.5 Frequency Domain Assumptions 120 6.6 Technical Appendix: Proofs 123 7 Sample Mean 127 7.1 Central Limit Theorem for I(0) Processes 127 7.2 Central Limit Theorem for I(d) Processes 129 7.3 Functional Central Limit Theory 132 7.4 Inference About the Mean 139 7.5 Sample Autocorrelation 141 7.6 Technical Appendix: Proofs 145 8 Parametric Estimators 149 8.1 Parametric Assumptions 149 8.2 Exact Maximum Likelihood Estimation 150 8.3 Conditional Sum of Squares 154 8.4 Parametric Whittle Estimation 156 8.5 Log-periodogram Regression of FEXP Processes 161 8.6 Fractionally Integrated Noise 164 8.7 Technical Appendix: Proofs 165 9 Semiparametric Estimators 169 9.1 Local Log-periodogram Regression 169 9.2 Local Whittle Estimation 175 9.3 Finite Sample Approximation 182 9.4 Bias Approximation and Reduction 184 9.5 Bandwidth Selection 188 9.6 Global Estimators 193 9.7 Technical Appendix: Proofs 195 10 Testing 197 10.1 Hypotheses on Fractional Integration 197 10.2 Rescaled Range or Variance 199 10.3 The Score Test Principle 204 10.4 Lagrange Multiplier (LM) Test 205 10.5 LM Test in the Frequency Domain 210 10.6 Regression-based LM Test 213 10.7 Technical Appendix: Proofs 218 11 Further Topics 223 11.1 Model Selection and Specification Testing 223 11.2 Spurious Long Memory 226 11.3 Forecasting 229 11.4 Cyclical and Seasonal Models 231 11.5 Long Memory in Volatility 234 11.6 Fractional Cointegration 236 11.7 R Packages 240 11.8 Neglected Topics 241 Bibliography 245 Index 267
Copyright Date
2018

Item description from the seller

AlibrisBooks

AlibrisBooks

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