Time series analysis:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Princeton, New Jersey
Princeton University Press
[1994]
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006431105&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006431105&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
| Umfang: | XIV, 799 Seiten Diagramme |
| ISBN: | 0691042896 9780691042893 |
Internformat
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| _version_ | 1821937049916145665 |
| adam_text | Time Series Analysis
JAMES D. HAMILTON
T
JL he last decade has brought dramatic changes
in the way that researchers analyze time series
data. This much-needed hook synthesizes all of
the major recent advances and develops a single,
coherent presentation of the current state of the
art of this increasingly important field. James
Hamilton provides for the first time a thorough
and detailed textbook account of important inno¬
vations such as vector autoregressions. estimation
by generalized method of moments.
and statistical consequences of unit roots, time-
varying variances, and nonlinear time series mod¬
els. In addition. Hamilton presents traditional tools
for analyzing dynamic systems, including linear
representations, autocovariance, generating func¬
tions, spectral analysis, and the
trating their usefulness both for economic theory
and for studying and interpreting real-world data.
This book is intended to provide students,
researchers, and forecasters with
self-contained survey of dynamic systems, econo¬
metrics, and time series analysis. Starting from
first principles. Hamilton* lucid presentation
makes both old and new developments accessible
to first-year graduate students and
Moreover, the works thoroughness and depth of
coverage will make Time Series Analysis an
(continued
inváuable
of the field. Hamilton achieves these dual objectives
by including numerous examples that illustrate
exactly how the theoretical results are used and
applied in practice, while relegating many details to
mathematical appendixes at the end of chapters. As
an intellectual roadmap of the field for students
and researchers alike, this volume promises to be
the authoritative guide for years to come.
JAMES D. HAMILTON is Professor of
Economics at the University of California, San
Diego. He holds a Ph.D. from the university of
California, Berkeley, and has previously taught at
the University of Virginia.
Contents
PREFACE
1
1.1.
1.2.
APPENDIX
References
2
2.1.
2.2.
2.3.
2.4.
2.5.
References
3
3.1.
3.2.
3.3.
3.4.
3.5.
Processes
3.6.
3.7.
APPENDIX 3.A. Convergence Results for Infinite-Order
Moving Average Processes
Exercises
4
4.1.
4.2.
of Observations
4.3.
of Observations
4.4.
Symmetric Matrix
4.5.
4.6.
4.7.
4.8.
Modeling Philosophy
APPENDIX 4.A. Parallel Between OLS Regression
and Linear Projection
APPENDIX 4.B. Triangular Factorization of the Covariance
Matrix for an MA(1) Process
Exercises
5
5.1.
5.2.
Process
5.3.
Process
5.4.
Process
5.5.
Process
5.6.
Process
5.7.
vi
5.8.
Estimation
5.9.
APPENDIX
Exercises
6
6.1.
6.2.
6.3.
6.4.
APPENDIX
Exercises
7
7.1.
7.2.
Observations
APPENDIX
Exercises
8
8.1.
with Deterministic Regressors and i.i.d. Gaussian
Disturbances
8.2.
Conditions
8.3.
APPENDIX
Exercises
9
9.1.
9.2.
Squares
Contents
9.3.
9.4.
Estimation
9.5.
9.6.
APPENDIX
Exercise
10
10.1.
10.2.
for Vector Processes
10.3.
for Vector Processes
10.4.
10.5.
APPENDIX
Exercises
11
11.1.
Testing for an Unrestricted Vector
Autoregression 291
11.2.
11.3.
Vector
11.4.
11.5.
11.6.
Models
11.7.
Functions
APPENDIX
APPENDIX
Exercises
viii
12
12.1.
12.2.
12.3.
APPENDIX
Exercise
13
13.1.
System
13.2.
13.3.
Representation
13.4.
of Parameters
13.5.
13.6.
13.7.
13.8.
APPENDIX 13.A. Proofs of Chapter
Exercises
14
14.1.
of Moments
14.2.
14.3.
14.4.
APPENDIX 14.A. Proofs of Chapter
Exercise
15
15.1.
15.2.
Contents
15.3.
Processes
15.4.
15.5.
APPENDIX
for Chapter
References
16
16.1.
of the Simple Time Trend Model
16.2.
Model
16.3.
Process Around a Deterministic Time Trend
APPENDIX
for Chapter
Exercises
17
17.1.
17.2.
17.3.
17.4.
Autoregression
Unity
17.5.
with General Serial Correlation
17.6.
17.7.
Autoregression
Tests for Unit Roots
17.8.
17.9.
APPENDIX
Exercises
X Contents
18
18.1.
Processes
18.2.
18.3.
APPENDIX
Exercises
19
19.1.
19.2.
Cointegration
19.3.
Vector
APPENDIX
Exercises
20
Analysis of Cointegrated Systems
20.1.
20.2.
20.3.
20.4.
or Not to Difference?
APPENDIX 20.A. Proofs of Chapter
Exercises
21
21.1.
(ARCH)
21.2.
APPENDIX 21.A. Derivation of Selected Equations
for Chapter
References
Contents
22
in Regime
22.1.
22.2.
22.3.
Distributions
22.4.
APPENDIX 22.A. Derivation of Selected Equations
for Chapter
Exercise
A Mathematical Review
A.I. Trigonometry
A.
A.3. Calculus
A.
A.
References
В
Answers to Selected Exercises
D
Used in the Text
AUTHOR INDEX
SUBJECT INDEX
ХІІ
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| dewey-search | 519.5/5 20 |
| dewey-sort | 3519.5 15 220 |
| dewey-tens | 510 - Mathematics |
| discipline | Soziologie Mathematik Wirtschaftswissenschaften |
| format | Book |
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| publishDate | 1994 |
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| spellingShingle | Hamilton, James D. 1954- Time series analysis Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4067486-1 |
| title | Time series analysis |
| title_auth | Time series analysis |
| title_exact_search | Time series analysis |
| title_full | Time series analysis James D. Hamilton |
| title_fullStr | Time series analysis James D. Hamilton |
| title_full_unstemmed | Time series analysis James D. Hamilton |
| title_short | Time series analysis |
| title_sort | time series analysis |
| topic | Time-series analysis Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Time-series analysis Zeitreihenanalyse |
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