Time series analysis and its applications: with R examples
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
2006
|
| Ausgabe: | 2. ed. |
| Schriftenreihe: | Springer texts in statistics
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIII, 575 S. Ill., graph. Darst. |
| ISBN: | 0387293175 9780387293172 |
Internformat
MARC
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| 100 | 1 | |a Shumway, Robert H. |e Verfasser |0 (DE-588)1231301228 |4 aut | |
| 245 | 1 | 0 | |a Time series analysis and its applications |b with R examples |c Robert H. Shumway ; David S. Stoffer |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York [u.a.] |b Springer |c 2006 | |
| 300 | |a XIII, 575 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Springer texts in statistics | |
| 650 | 4 | |a Zeitreihenanalyse | |
| 650 | 4 | |a Série chronologique | |
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| 650 | 4 | |a Time-series analysis | |
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Datensatz im Suchindex
| _version_ | 1817062368250691584 |
|---|---|
| adam_text |
Contents
Characteristics
of Time Series
1
1.1
Introduction
. 1
1.2
The Nature of Time Series Data
. 4
1.3
Time Series Statistical Models
. 11
1.4
Measures of Dependence: Autocorrelation
and Cross-Correlation
. 18
1.5
Stationary Time Series
. 23
1.6
Estimation of Correlation
. 29
1.7
Vector-Valued and Multidimensional Series
. 34
Problems
. 40
Time Series Regression and Exploratory Data Analysis
48
2.1
Introduction
. 48
2.2
Classical Regression in the Time Series Context
. 49
2.3
Exploratory Data Analysis
. 57
2.4
Smoothing in the Time Series Context
. 71
Problems
. 79
ARIMA Models
84
3.1
Introduction
. 84
3.2
Autoregressive
Moving Average Models
. 85
3.3
Difference Equations
. 98
3.4
Autocorrelation and Partial Autocorrelation Functions
. 103
3.5
Forecasting
. 110
3.6
Estimation
. 122
3.7
Integrated Models for Nonstationary Data
. 140
3.8
Building ARIMA Models
. 143
3.9
Multiplicative Seasonal ARIMA Models
. 154
Problems
. 165
Spectral Analysis and Filtering
174
4.1
Introduction
. 174
4.2
Cyclical Behavior and Periodicity
. 176
4.3
The Spectral Density
. 181
xii
Contents
4.4
Periodogram
and Discrete Fourier Transform
. 187
4.5
Nonparametric Spectral Estimation
. 197
4.6
Multiple Series and Cross-Spectra
. 215
4.7
Linear Filters
. 220
4.8
Parametric Spectral Estimation
. 228
4.9
Dynamic Fourier Analysis and Wavelets
. 232
4.10
Lagged Regression Models
. 245
4.11
Signal Extraction and Optimum Filtering
. 251
4.12
Spectral Analysis of Multidimensional Series
. 256
Problems
. 258
5
Additional Time Domain Topics
271
5.1
Introduction
. 271
5.2
Long Memory
ARMA
and Fractional Differencing
. 271
5.3
GARCH Models
. 280
5.4
Threshold Models
. 289
5.5
Regression with Autocorrelated Errors
. 293
5.6
Lagged Regression: Transfer Function Modeling
. 295
5.7
Multivariate ARMAX Models
. 302
Problems
. 320
6
State-Space Models
324
6.1
Introduction
. 324
6.2
Filtering, Smoothing, and Forecasting
. 330
6.3
Maximum Likelihood Estimation
. 339
6.4
Missing Data Modifications
. 348
6.5
Structural Models: Signal Extraction and Forecasting
. 352
6.6
ARMAX Models in State-Space Form
. 355
6.7
Bootstrapping State-Space Models
. 357
6.8
Dynamic Linear Models with Switching
. 362
6.9
Nonlinear and Non-normal State-Space
Models Using Monte Carlo Methods
. 376
6.10
Stochastic Volatility
. 388
6.11
State-Space and ARMAX Models for
Longitudinal Data Analysis
. 394
Problems
. 404
7
Statistical Methods in the Frequency Domain
412
7.1
Introduction
. 412
7.2
Spectral Matrices and Likelihood Functions
. 416
7.3
Regression for Jointly Stationary Series
. 417
7.4
Regression with Deterministic Inputs
. 426
7.5
Random Coefficient Regression
. 434
7.6
Analysis of Designed Experiments
. 438
7.7
Discrimination and Cluster Analysis
. 449
Contents xiii
7.8 Principal
Components and Factor Analysis
. 464
7.9
The Spectral Envelope
. 479
Problems
. 495
Appendix A: Large Sample Theory
501
A.I Convergence Modes
. 501
A.2 Central Limit Theorems
. 509
A.3 The Mean and Autocorrelation Functions
. 513
Appendix B: Time Domain Theory
522
B.I Hubert Spaces and the Projection Theorem
. 522
B.2 Causal Conditions for
ARMA
Models
. 526
B.3 Large Sample Distribution of the AR(p)
Conditional Least Squares Estimators
. 528
B.4 The Wold Decomposition
. 532
Appendix C: Spectral Domain Theory
534
C.I Spectral Representation Theorem
. 534
C.2 Large Sample Distribution of the DFT and
Smoothed
Periodogram
. 539
C.3 The Complex Multivariate Normal Distribution
. 550
References
555
Index
569 |
| adam_txt |
Contents
Characteristics
of Time Series
1
1.1
Introduction
. 1
1.2
The Nature of Time Series Data
. 4
1.3
Time Series Statistical Models
. 11
1.4
Measures of Dependence: Autocorrelation
and Cross-Correlation
. 18
1.5
Stationary Time Series
. 23
1.6
Estimation of Correlation
. 29
1.7
Vector-Valued and Multidimensional Series
. 34
Problems
. 40
Time Series Regression and Exploratory Data Analysis
48
2.1
Introduction
. 48
2.2
Classical Regression in the Time Series Context
. 49
2.3
Exploratory Data Analysis
. 57
2.4
Smoothing in the Time Series Context
. 71
Problems
. 79
ARIMA Models
84
3.1
Introduction
. 84
3.2
Autoregressive
Moving Average Models
. 85
3.3
Difference Equations
. 98
3.4
Autocorrelation and Partial Autocorrelation Functions
. 103
3.5
Forecasting
. 110
3.6
Estimation
. 122
3.7
Integrated Models for Nonstationary Data
. 140
3.8
Building ARIMA Models
. 143
3.9
Multiplicative Seasonal ARIMA Models
. 154
Problems
. 165
Spectral Analysis and Filtering
174
4.1
Introduction
. 174
4.2
Cyclical Behavior and Periodicity
. 176
4.3
The Spectral Density
. 181
xii
Contents
4.4
Periodogram
and Discrete Fourier Transform
. 187
4.5
Nonparametric Spectral Estimation
. 197
4.6
Multiple Series and Cross-Spectra
. 215
4.7
Linear Filters
. 220
4.8
Parametric Spectral Estimation
. 228
4.9
Dynamic Fourier Analysis and Wavelets
. 232
4.10
Lagged Regression Models
. 245
4.11
Signal Extraction and Optimum Filtering
. 251
4.12
Spectral Analysis of Multidimensional Series
. 256
Problems
. 258
5
Additional Time Domain Topics
271
5.1
Introduction
. 271
5.2
Long Memory
ARMA
and Fractional Differencing
. 271
5.3
GARCH Models
. 280
5.4
Threshold Models
. 289
5.5
Regression with Autocorrelated Errors
. 293
5.6
Lagged Regression: Transfer Function Modeling
. 295
5.7
Multivariate ARMAX Models
. 302
Problems
. 320
6
State-Space Models
324
6.1
Introduction
. 324
6.2
Filtering, Smoothing, and Forecasting
. 330
6.3
Maximum Likelihood Estimation
. 339
6.4
Missing Data Modifications
. 348
6.5
Structural Models: Signal Extraction and Forecasting
. 352
6.6
ARMAX Models in State-Space Form
. 355
6.7
Bootstrapping State-Space Models
. 357
6.8
Dynamic Linear Models with Switching
. 362
6.9
Nonlinear and Non-normal State-Space
Models Using Monte Carlo Methods
. 376
6.10
Stochastic Volatility
. 388
6.11
State-Space and ARMAX Models for
Longitudinal Data Analysis
. 394
Problems
. 404
7
Statistical Methods in the Frequency Domain
412
7.1
Introduction
. 412
7.2
Spectral Matrices and Likelihood Functions
. 416
7.3
Regression for Jointly Stationary Series
. 417
7.4
Regression with Deterministic Inputs
. 426
7.5
Random Coefficient Regression
. 434
7.6
Analysis of Designed Experiments
. 438
7.7
Discrimination and Cluster Analysis
. 449
Contents xiii
7.8 Principal
Components and Factor Analysis
. 464
7.9
The Spectral Envelope
. 479
Problems
. 495
Appendix A: Large Sample Theory
501
A.I Convergence Modes
. 501
A.2 Central Limit Theorems
. 509
A.3 The Mean and Autocorrelation Functions
. 513
Appendix B: Time Domain Theory
522
B.I Hubert Spaces and the Projection Theorem
. 522
B.2 Causal Conditions for
ARMA
Models
. 526
B.3 Large Sample Distribution of the AR(p)
Conditional Least Squares Estimators
. 528
B.4 The Wold Decomposition
. 532
Appendix C: Spectral Domain Theory
534
C.I Spectral Representation Theorem
. 534
C.2 Large Sample Distribution of the DFT and
Smoothed
Periodogram
. 539
C.3 The Complex Multivariate Normal Distribution
. 550
References
555
Index
569 |
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| author | Shumway, Robert H. Stoffer, David S. |
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| id | DE-604.BV021549234 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:30:59Z |
| indexdate | 2024-11-29T13:08:31Z |
| institution | BVB |
| isbn | 0387293175 9780387293172 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014765335 |
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| spelling | Shumway, Robert H. Verfasser (DE-588)1231301228 aut Time series analysis and its applications with R examples Robert H. Shumway ; David S. Stoffer 2. ed. New York [u.a.] Springer 2006 XIII, 575 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer texts in statistics Zeitreihenanalyse Série chronologique Tijdreeksen. gtt Time-series analysis Toepassingen. gtt Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 s DE-604 Stoffer, David S. Verfasser (DE-588)1050751000 aut Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014765335&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Shumway, Robert H. Stoffer, David S. Time series analysis and its applications with R examples Zeitreihenanalyse Série chronologique Tijdreeksen. gtt Time-series analysis Toepassingen. gtt Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4067486-1 |
| title | Time series analysis and its applications with R examples |
| title_auth | Time series analysis and its applications with R examples |
| title_exact_search | Time series analysis and its applications with R examples |
| title_exact_search_txtP | Time series analysis and its applications with R examples |
| title_full | Time series analysis and its applications with R examples Robert H. Shumway ; David S. Stoffer |
| title_fullStr | Time series analysis and its applications with R examples Robert H. Shumway ; David S. Stoffer |
| title_full_unstemmed | Time series analysis and its applications with R examples Robert H. Shumway ; David S. Stoffer |
| title_short | Time series analysis and its applications |
| title_sort | time series analysis and its applications with r examples |
| title_sub | with R examples |
| topic | Zeitreihenanalyse Série chronologique Tijdreeksen. gtt Time-series analysis Toepassingen. gtt Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Zeitreihenanalyse Série chronologique Tijdreeksen. Time-series analysis Toepassingen. |
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