The practice of time series analysis:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
1999
|
| Schriftenreihe: | Statistics for engineering and physical science
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XVIII, 386 S. graph. Darst. |
| ISBN: | 0387986588 |
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| 245 | 1 | 0 | |a The practice of time series analysis |c Hirotugu Akaike ... eds. |
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Datensatz im Suchindex
| _version_ | 1804127098085834752 |
|---|---|
| adam_text | IMAGE 1
HIROTUGU AKAIKE
GENSHIRO KITAGAWA EDITORS
THE PRACTICE OF
TIME SERIES ANALYSIS
SPRINGER
IMAGE 2
CONTENTS
PREFACE TO THE ENGLISH VERSION V
PREFACE VII
THE STRUCTURE OF THIS BOOK AND GENERAL REFERENCES IX
1 CONTROL OF BOILERS FOR THERMOELECTRIC POWER PLANTS BY MEANS OF A
STATISTICAL MODEL 1
HIDEO NAKAMURA
1.1 INTRODUCTION 1
1.2 PROBLEMS IN CONTROLLING MULTIVARIABLE SYSTEM 2
1.3 SYSTEM ANALYSIS AND CONTROL BY MEANS OF STATISTICAL MODEL 4
1.4 PRACTICAL PROCEDURE FOR OPTIMAL CONTROLLER DESIGN 6
1.5 APPLICATION RESULTS AT ACTUAL PLANTS 13
1.6 CLOSING REMARKS 15
2 FEEDBACK ANALYSIS OF A LIVING BODY BY A MULTIVARIATE AUTOREGRESSIVE
MODEL 19
TAKAO WADA
2.1 INTRODUCTION 19
2.2 BODY LIQUID CONTROL AND FEEDBACK 20
2.3 EXAMPLE OF THE RELATIVE POWER CONTRIBUTION AND IMPULSE RESPONSE * *
23 2.4 USING AN AUTOREGRESSIVE MODEL FOR FEEDBACK ANALYSIS 25
2.5 OBTAINING THE POWER CONTRIBUTION 26
2.6 STATE EQUATION AND IMPULSE RESPONSE 27
2.7 IMPULSE RESPONSE OF THE CLOSED AND OPEN SYSTEMS 29
2.8 CONFIRMATION BY A VIRTUAL FEEDBACK SYSTEM 31
2.9 CONCLUSIONS 34
IMAGE 3
XUE CONTENTS
3 FACTOR DECOMPOSITION OF ECONOMIC TIME SERIES FLUCTUATIONS - ECONOMIC
AND STATISTICAL MODELS IN HARMONY 37
KOSEI FUKUDA
3.1 INTRODUCTION 37
3.2 MODEL 1 (MODEL WITH STOCHASTIC COMPONENTS ONLY) 38
3.3 MODEL 2 (THE MODEL INCLUDING DETERMINISTIC COMPONENTS) 42
3.4 MODEL 3 (THE MODEL BY WHICH MACROECONOMIC POLICY EFFECT CAN ALSO BE
MEASURED) 46
3.5 HAS FINE TUNING BEEN SUCCESSFUL? 50
3.6 IS PREDICTION ABILITY AVAILABLE? 52
3.7 CONCLUSIONS AND SUBJECTS IN THE FUTURE 53
4 THE STATISTICAL OPTIMUM CONTROL OF SHIP MOTION AND A MARINE MAIN
ENGINE 57
KOHEI OHTSU
4.1 INTRODUCTION 57
4.2 OUTLINE OF THE CONTROL OF THE MOTION OF THE HUU AND MAIN ENGINE * *
58 4.3 STATISTICAL MODEL OF SHIP MOTIONS AND ITS CONTROL 60
4.4 DESIGN OF OPTIMUM AUTOPILOT SYSTEM BASED ON THE CONTROL-TYPE
AUTOREGRESSIVE MODEL 62
4.5 NOISE-ADAPTIVE CONTROL SYSTEM 68
4.6 RUDDER-ROLL CONTROL SYSTEM 71
4.7 APPLICATION TO THE MARINE MAIN ENGINE GOVERNOR SYSTEM 72
4.8 CONCLUSIONS 75
5 HIGH PRECISION ESTIMATION OF SEISMIC WAVE ARRIVAL TIMES 79
TETSUO TAKANAMI
5.1 INTRODUCTION 79
5.2 LOCALLY STATIONARY AR MODEL 80
5.3 AUTOMATIC DIVISION OF A LOCALLY STATIONARY INTERVAL 83
5.4 PRECISION ESTIMATION OF SEISMIC WAVE ARRIVAL TIMES 85
5.5 APPLICATION: EARTHQUAKE LOCATION AND VELOCITY STRUCTURE DETERMINA
TION FROM PRECISE ARRIVAL TIME ESTIMATES 86
5.6 CONCLUSIONS 92
6 ANALYSIS OF DYNAMIC CHARACTERISTICS OF A DRIVER-VEHICLE SYSTEM 95
HITOSHI SOMA
6.1 INTRODUCTION 95
6.2 DYNAMICS OF AUTOMOBILE UNDER LATERAL-WIND DISTURBANCE 96
6.3 APPLICATION OF MULTIVARIATE AR MODEL TO DRIVER-VEHICLE SYSTEM * * *
* 102 6.4 DYNAMICS OF DRIVER-VEHICLE SYSTEM UNDER LATERAL-WIND 106
6.5 CONCLUSIONS 112
IMAGE 4
CONTENTS XUEI
7 ESTIMATION OF DIRECTIONAL WAVE SPECTRA USING SHIP MOTION DATA 115
TOSHIO ISEKI
7.1 INTRODUCTION 115
7.2 CROSS-SPECTRUM ANALYSIS BY A MULTIVARIATE AR MODEL 116
7.3 RELATION BETWEEN THE DIRECTIONAL WAVE SPECTRUM AND THE SHIP MOTIONS
- 1 20
7.4 ESTIMATION OF THE DIRECTIONAL WAVE SPECTRUM USING A BAYESIAN MODEL
122
7.5 RESULTS OF THE TANK TEST USING A MODEL SHIP 124
7.6 CONCLUSIONS 128
8 CONTROL OF FILATURE PRODUCTION PROCESS 131
AKINORI SHIMAZAKI
8.1 DROPPING-END CONTROL AND GAP PROCESS 131
8.2 SIZE CONTROL OF RAW SILK 137
8.3 DWELL TIME IN A BLACK BOX 144
9 APPLICATION TO PHARMACOKINETIC ANALYSIS 153
AKIFUMI YAFUNE
9.1 INTRODUCTION 153
9.2 PHARMACOKINETIC MODEL 154
9.3 MONTE CARLO ESTIMATION OF MAXIMUM LOG LIKELIHOOD * * * * *. 155
9.4 EXAMPLE 157
9.5 CONCLUDING REMARKS 160
10 STATE SPACE MODELING OF SWITCHING TIME SERIES 163
FUMIYASU KOMAKI
10.1 INTRODUCTION * * * * 163
10.2 TIME SERIES DATA WITH PULSES AND THE EXISTING METHODS 164
10.3 THE STATE SPACE MODEL FOR TIME SERIES WITH PULSES 166
10.4 CONCLUSIONS 172
11 TIME VARYING COEFFICIENT AR AND VAR MODELS 175
XING-QI MANG
11.1 INTRODUCTION 175
11.2 TIME VARYING COEFFICIENT AR MODELS 176
11.3 TIME VARYING COEFFICIENT VAR MODELS 180
11.4 AN EXAMPLE OF SEISMIC DATA ANALYSIS 183
IMAGE 5
XIV CONTENTS
12 STATISTICAL CONTROL OF CEMENT PROCESS 193
YOSHITAKA YAGIHAM
12.1 INTRODUCTION 193
12.2 CEMENT PLANT 194
12.3 IDENTIFICATION AND CONTROL OF THE KILN PROCESS 196
12.4 COUECTION AND IDENTIFICATION OF THE DATA UNDER THE ON-LINE CONTROL
* * 204 12.5 OPTIMAL PRODUCTION LEVEL AND PURSUIT CONTROL 204
12.6 CONCLUSIONS 206
13 ANALYSIS OF A HUMAN/2-WHEELED-VEHICLE SYSTEM BY ARDOCK 209
MAKIO ISHIGURO AND TAKAO OYA
13.1 INTRODUCTION 209
13.2 DATA 211
13.3 AR MODEL AND ARDOCK 214
13.4 NUMERICAL RESULTS 215
13.5 ANALYSIS OF THE HANDS-FREE STEERING 222
13.6 THE OPTIMUM CONTROL 225
14 VIBRATION DATA ANALYSIS OF AUTOMOBILES 229
SHINZI YAMAKAWA
14.1 PREFACE 229
14.2 ROAD SURFACE INPUT-WEAR OF COMPONENT MATERIAL AND FADING COMFORT
230
14.3 SEPARATION OF CORRELATED POWER COMPONENTS IN A MULTIPLE INPUT
SYSTEM BY MEANS OF POWER CONTRIBUTIONS 232
14.4 DECISION OF CONTINUITY OF DATA PROPERTIES 235
14.5 IDENTIFICATION OF NONLINEAR VIBRATION SYSTEM THROUGH BISPECTRAL
ANALYSIS 236
14.6 CONTINUOUS MEASUREMENT OF TIME-VARIANT SPECTRUM 240
14.7 AFTERWORD 243
15 AUTO-REGRESSIVE SPECTRAL ANALYSIS OF RR-INTERVAL TIME SERIES IN
HEALTHY FETUS AND NEWBORN INFANTS 247
TERUYUKI OGAWA
15.1 INTRODUCTION 247
15.2 SUBJECTS AND METHODS 247
15.3 RESULTS 253
15.4 DISCUSSION 256
15.5 CONCLUSIONS 258
IMAGE 6
CONTENTS
XV
16 INFORMATION PROCESSING MECHANISMS IN THE MAMMALIAN
BRAIN: ANALYSIS OF SPATIO-TEMPORAL NEURAL RESPONSE IN THE AUDITORY
CORTEX 263
KOHYU FUKUNISHI
16.1 INTRODUCTION * * 263
16.2 INSTRUMENTATION OF AND INFORMATION PROCESSING IN THE BRAIN 264
16.3 OPTICAL MULTIPOINT OBSERVATION IN THE MAMMALIAN AUDITORY CORTEX 265
16.4 SPATIO-TEMPORAL NEURAL ACTIVITY OBSERVATION 266
16.5 FUNCTIONAL MODULES IN THE AUDITORY CORTEX 270
16.6 PATTERN TIME SERIES ANALYSIS 272
16.7 NEURAL CORRELATION OF AND NEURAL BINDING 273
16.8 EVALUATION OF CORTICAL NEURAL BINDING 274
16.9 CHARACTERISTICS OF STATIONARY STOCHASTIC RESPONSE 279
16.10 CONCLUSIONS 280
17 TIME SERIES ANALYSIS OF FINANCIAL ASSET PRICE FLUCTUATIONS 285
HIROSHI TSUDA
17.1 INTRODUCTION 283
17.2 NONSTATIONARY NATURE OF FINANCIAL ASSET PRICES 283
17.3 MULTIVARIATE ANALYSIS OF THE TIME SERIES MODEL 288
17.4 CONCLUSION 297
18 DYNAMIC ANALYSIS OF ECONOMIC TIME SERIES 299
SADAO NANIWA
18.1 INTRODUCTION 299
18.2 TREND OF THE ECONOMIC TIME SERIES AND THE FLUCTUATION AROUND THE
TREND 300
18.3 ANALYSIS OF ABRUPT CHANGE OF TREND 304
18.4 ANALYSIS OF THE ECONOMIC SYSTEM BY A MULTIVARIATE NONSTATIONARY
TIME SERIES MODEL 307
18.5 CONCLUSIONS 311
19 PROCESSING OF TIME SERIES DATA OBTAINED BY SATELLITES 313
TOMOYUHI HIGUCHI
19.1 INTRODUCTION 313
19.2 PROBLEMS TO BE DEALT WITH 314
19.3 APPROACH BY A BAYESIAN MODEL -SIMPLE MODEL 316
19.4 EXAMPLE OF A SIMPLE MODEL 321
19.5 POINT NOISE SOURCE MODEL 322
19.6 CONCLUSIONS 326
IMAGE 7
XVI CONTENTS
20 ANALYSIS OF EARTH TIDES DATA 327
YOSHIAKI TAMARA
20.1 WHAT ARE EARTH TIDES? * * * 327
20.2 ANALYSIS MODEL 329
20.3 TIDAL ANALYSIS PROGRAM BAYTAP-G 334
20.4 FOCAL POINTS IN THE ANALYSIS 337
20.5 CONCLUDING REMARKS 338
21 DETECTION OF GROUNDWATER LEVEL CHANGES RELATED TO EARTHQUAKES 341
NORIO MATSUMOTO
21.1 INTRODUCTION 341
21.2 OBSERVATION DATA 342
21.3 DATA ANALYSIS METHOD 342
21.4 ANALYSIS OF ACTUAL DATA 346
21.5 CONCLUSIONS 350
22 PROCESSING OF MISSING OBSERVATIONS AND OUTLIERS IN TIME SERIES 353
GENSHIRO KITAGAWA
22.1 MISSING OBSERVATIONS AND OUTLIERS 353
22.2 PROCESSING OF MISSING OBSERVATIONS 355
22.3 PROCESSING OF OUTLIERS 360
22.4 CONCLUSIONS 364
23 MENTAL PREPARATION FOR TIME SERIES ANALYSIS 367
HIROTUGU AKAIKE
23.1 INTRODUCTION 367
23.2 TIME SERIES ANALYSIS AND STATISTICAL SCIENCE 367
23.3 PREDICTION AND EXPECTATION 368
23.4 ULTIMATE TRUTH AND MODELS 368
23.5 EVALUATION OF A MODEL AND INFORMATION CRITERION 369
23.6 CONFIRMATION OF VALIDITY 370
23.7 CONCLUSIONS 371
APPENDIX 373
INDEX 381
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| title | The practice of time series analysis |
| title_auth | The practice of time series analysis |
| title_exact_search | The practice of time series analysis |
| title_full | The practice of time series analysis Hirotugu Akaike ... eds. |
| title_fullStr | The practice of time series analysis Hirotugu Akaike ... eds. |
| title_full_unstemmed | The practice of time series analysis Hirotugu Akaike ... eds. |
| title_short | The practice of time series analysis |
| title_sort | the practice of time series analysis |
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