Applied time series analysis: a practical guide to modeling and forecasting
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
London
Elsevier, Academic Press
[2019]
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xiii, 339 Seiten Diagramme |
| ISBN: | 9780128131176 |
Staff View
MARC
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| 245 | 1 | 0 | |a Applied time series analysis |b a practical guide to modeling and forecasting |c Terence C. Mills (Loughborough University, Loughborough, United Kingdom) |
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Record in the Search Index
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| adam_text | Contents
Introduction ix
1. Time Series and Their Features 1
Autocorrelation and Periodic Movements 2
Seasonality 4
Stationarity and Nonstationarity 4
Trends 6
Volatility 8
Common Features 9
Time Series Having Natural Constraints 10
Endnotes 12
2. Transforming Time Series 13
Distributional Transformations 13
Stationarity Inducing Transformations 20
Decomposing a Time Series and Smoothing Transformations 23
Endnotes 30
3. ARMA Models for Stationary Time Series 31
Stochastic Processes and Stationarity 31
Wold s Decomposition and Autocorrelation 33
First-Order Autoregressive Processes 35
First-Order Moving Average Processes 36
General AR and MA Processes 37
Autoregressive-Moving Average Models 43
ARMA Model Building and Estimation 46
Endnotes 55
4. ARIMA Models for Nonstationary Time Series 57
Nonstationarity 57
ARIMA Processes 60
ARIMA Modeling 65
Endnotes 68
v
vi Contents
5. Unit Roots, Difference and Trend Stationarity,
and Fractional Differencing 71
Determining the Order of Integration of a Time Series 71
Testing for a Unit Root 73
Trend Versus Difference Stationarity 77
Testing for More Than One Unit Root 81
Other Approaches to Testing for a Unit Root 83
Estimating Trends Robustly 87
Fractional Differencing and Long Memory 90
Testing for Fractional Differencing 93
Estimating the Fractional Differencing Parameter 96
Endnotes 101
6. Breaking and Nonlinear Trends 103
Breaking Trend Models 103
Breaking Trends and Unit Root Tests 105
Unit Roots Tests When the Break Date Is Unknown 110
Robust Tests for a Breaking Trend 111
Confidence Intervals for the Break Date and Multiple Breaks 112
Nonlinear Trends 112
Endnotes 119
7. An Introduction to Forecasting With Univariate
Models 121
Forecasting With Autoregressive-Integrated-Moving Average
(ARIMA) Models 121
Forecasting a Trend Stationary Process 128
Endnotes 130
8. Unobserved Component Models, Signal Extraction,
and Filters 131
Unobserved Component Models 131
Signal Extraction 136
Filters 139
Endnotes 144
9. Seasonality and Exponential Smoothing 145
Seasonal Patterns in Time Series 145
Modeling Deterministic Seasonality 145
Modeling Stochastic Seasonality 147
Mixed Seasonal Models 152
Seasonal Adjustment 1 53
Exponential Smoothing 153
Endnotes 159
Contents vii
10. Volatility and Generalized Autoregressive
Conditional Heteroskedastic Processes 161
Volatility 161
Autoregressive Conditional Heteroskedastic Processes 163
Testing for the Presence of ARCH Errors 165
Forecasting From an ARMA-GARCH Model 168
Endnotes 171
11. Nonlinear Stochastic Processes 173
Martingales, Random Walks, and Nonlinearity 173
Nonlinear Stochastic Models 1 76
Bilinear Models 1 77
Threshold and Smooth Transition Autoregressions 181
Markov-Switching Models 185
Neural Networks 188
Nonlinear Dynamics and Chaos 189
Testing for Nonlinearity 192
Forecasting With Nonlinear Models 198
Endnotes 199
12. Transfer Functions and Autoregressive Distributed
Lag Modeling 201
Transfer Function-Noise Models 201
Autoregressive Distributed Lag Models 203
Endnotes 210
13. Vector Autoregressions and Granger Causality 211
Multivariate Dynamic Regression Models 211
Vector Autoregressions 212
G range r Causa! ity 213
Determining the Lag Order of a Vector Autoregression 213
Variance Decompositions and Innovation Accounting 216
Structural Vector Autoregressions 222
Endnotes 230
14. Error Correction, Spurious Regressions, and
Cointegration 233
The Error Correction Form of an Autoregressive Distributed
Lag Model 233
Spurious Regressions 234
Error Correction and Cointegration 242
Testing for Cointegration 247
Estimating Cointegrating Regressions 250
Endnotes 253
viii Contents
15. Vector Autoregressions With Integrated Variables,
Vector Error Correction Models, and Common Trends 255
Vector Autoregressions With Integrated Variables 255
Vector Autoregressions With Cointegrated Variables 257
Estimation of Vector Error Correction Models and Tests
of Cointegrating Rank 260
Identification of Vector Error Correction Models 264
Structural Vector Error Correction Models 266
Causality Testing in Vector Error Correction Models 268
Impulse Response Asymptotics in Nonstationary VARs 269
Vector Error Correction Model-X Models 271
Common Trends and Cycles 274
Endnotes 279
16. Compositional and Count Time Series 281
Constrained Time Series 281
Modeling Compositional Data 281
Forecasting Compositional Time Series 283
Time Series Models for Counts: The IN-AR(1) Benchmark Model 288
Other Integer-Valued ARMA Processes 289
Estimation of Integer-Valued ARMA Models 290
Testing for Serial Dependence in Count Time Series 291
Forecasting Counts 293
Intermittent and Nonnegative Time Series 296
Endnotes 296
17. State Space Models 299
Formulating State Space Models 299
The Kalman Filter 303
ML Estimation and the Prediction Error Decomposition 305
Prediction and Smoothing 307
Multivariate State Space Models 308
Endnotes 309
18. Some Concluding Remarks 311
Endnotes 313
References 315
Index 329
|
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| id | DE-604.BV045504728 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:19:56Z |
| institution | BVB |
| isbn | 9780128131176 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030889357 |
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| owner_facet | DE-355 DE-BY-UBR |
| physical | xiii, 339 Seiten Diagramme |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier, Academic Press |
| record_format | marc |
| spelling | Mills, Terence C. 1952- Verfasser (DE-588)129450790 aut Applied time series analysis a practical guide to modeling and forecasting Terence C. Mills (Loughborough University, Loughborough, United Kingdom) London Elsevier, Academic Press [2019] xiii, 339 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 s b DE-604 Erscheint auch als Online-Ausgabe, ePub 978-0-12-813118-3 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030889357&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mills, Terence C. 1952- Applied time series analysis a practical guide to modeling and forecasting Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4067486-1 |
| title | Applied time series analysis a practical guide to modeling and forecasting |
| title_auth | Applied time series analysis a practical guide to modeling and forecasting |
| title_exact_search | Applied time series analysis a practical guide to modeling and forecasting |
| title_full | Applied time series analysis a practical guide to modeling and forecasting Terence C. Mills (Loughborough University, Loughborough, United Kingdom) |
| title_fullStr | Applied time series analysis a practical guide to modeling and forecasting Terence C. Mills (Loughborough University, Loughborough, United Kingdom) |
| title_full_unstemmed | Applied time series analysis a practical guide to modeling and forecasting Terence C. Mills (Loughborough University, Loughborough, United Kingdom) |
| title_short | Applied time series analysis |
| title_sort | applied time series analysis a practical guide to modeling and forecasting |
| title_sub | a practical guide to modeling and forecasting |
| topic | Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Time-series analysis Zeitreihenanalyse |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030889357&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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