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\def\WIPO{World Intellectual Property Organisation}
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Applied Bayesian forecasting and time series analysis / Andy Pole, Mike West, Jeff Harrison.
1994
A 9 POL.A
Available at WIPO Library
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Details
Title
Applied Bayesian forecasting and time series analysis / Andy Pole, Mike West, Jeff Harrison.
Description
xviii, 409 pages : illustrations ; 24 cm + 1 computer disc (3 1/2 in.).
ISBN
0412044013
9780412044014
9781489934321 electronic book
1489934324 electronic book
9781482267433 electronic book
1482267438 electronic book
0412988313 Diskette
9780412988318 Diskette
9780412044013
9780412044014
9781489934321 electronic book
1489934324 electronic book
9781482267433 electronic book
1482267438 electronic book
0412988313 Diskette
9780412988318 Diskette
9780412044013
Alternate Call Number
A 9 POL.A
Summary
This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts. This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts.;Examination of real time series motivates concepts such as component decomposition, fundamental model forms such as trends and cycles, and practical modelling requirements such as dealing coherently with routine change and unusual events. The concepts, model forms, and modelling requirements are unified in the framework of the dynamic linear mode.;A complete theoretical development of the DLM is presented, with each step along the way demonstrated with analysis of real time series. Inference is made within the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations.;An integral part of the book is the BATS software program. BATS is supplied in both DOS and Windows versions. Completely menu driven, BATS provides all of the modelling facilities discussed and exemplified in the book. Indeed, all the analyses in the book are performed with the program.;There are also over 50 data sets in the book. Several are studied as detailed applications; several more are presented with preliminary analyses as starting points for detailed exercises. These data sets are included on the BATS diskette in the ASCII format.;This book should be of interest to researchers, practitioners, and advanced students in statistic operations research and engineering.
Note
Contents : Part A. Dynamic bayesian modelling : theory and applications : 1. Practical modelling and forecasting; 2. Methodological framework; 3. Analysis of the DLM; 4. Application : turkey chick sales; 5. Application : market share; 6. Application : marriages in Greece; 7. Further examples and exercises; Part B. Interactive time series analysis and forecasting : 8. Installing BATS; 9. Tutorial : introduction to BATS; 10. Tutorial : introduction to modelling; 11. Tutorial : advanced modelling; 12. Tutorial : modelling with incomplete data; 13. Tutorial : data management; Part C. BATS reference : 14. Communications; 15. Menu descriptions;.
Computer disk contains BATS : Bayesian analysis of time series. DOS and Windows versions 2.1.
1ère éd. New York : Chapman and Hall, cop. 1994.
Originally published: New York : Chapman and Hall, c1994.
This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts. This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts.;Examination of real time series motivates concepts such as component decomposition, fundamental model forms such as trends and cycles, and practical modelling requirements such as dealing coherently with routine change and unusual events. The concepts, model forms, and modelling requirements are unified in the framework of the dynamic linear mode.;A complete theoretical development of the DLM is presented, with each step along the way demonstrated with analysis of real time series. Inference is made within the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations.;An integral part of the book is the BATS software program. BATS is supplied in both DOS and Windows versions. Completely menu driven, BATS provides all of the modelling facilities discussed and exemplified in the book. Indeed, all the analyses in the book are performed with the program.;There are also over 50 data sets in the book. Several are studied as detailed applications; several more are presented with preliminary analyses as starting points for detailed exercises. These data sets are included on the BATS diskette in the ASCII format.;This book should be of interest to researchers, practitioners, and advanced students in statistic operations research and engineering.
Computer disk contains BATS : Bayesian analysis of time series. DOS and Windows versions 2.1.
1ère éd. New York : Chapman and Hall, cop. 1994.
Originally published: New York : Chapman and Hall, c1994.
This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts. This book discusses the practical forecasting and analysis of time series. It addresses the question of how to analyze time series data: how to identify structure, how to explain observed behavior, how to model those structures and behaviours, and how to use the insights gained from the analysis to make informed forecasts.;Examination of real time series motivates concepts such as component decomposition, fundamental model forms such as trends and cycles, and practical modelling requirements such as dealing coherently with routine change and unusual events. The concepts, model forms, and modelling requirements are unified in the framework of the dynamic linear mode.;A complete theoretical development of the DLM is presented, with each step along the way demonstrated with analysis of real time series. Inference is made within the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations.;An integral part of the book is the BATS software program. BATS is supplied in both DOS and Windows versions. Completely menu driven, BATS provides all of the modelling facilities discussed and exemplified in the book. Indeed, all the analyses in the book are performed with the program.;There are also over 50 data sets in the book. Several are studied as detailed applications; several more are presented with preliminary analyses as starting points for detailed exercises. These data sets are included on the BATS diskette in the ASCII format.;This book should be of interest to researchers, practitioners, and advanced students in statistic operations research and engineering.
Bibliography, etc. Note
Includes bibliographical references and index.
Formatted Contents Note
Dynamic Bayesian modelling : theory and applications
Practical modeling and forecasting
Methodological framework
Analysis of the DLM
Application : turkey chick sales
Application: market share
Application : marriages in Greece
Further examples and exercises
Interactive time series analysis and forecasting
Installing BATS
Tutorial : introduction to BATS
Tutorial : introduction to modelling
Tutorial : advanced modelling
Tutorial : modelling with incomplete data
Tutorial : data management
BATS reference
Communications
Menu descriptions.
Practical modeling and forecasting
Methodological framework
Analysis of the DLM
Application : turkey chick sales
Application: market share
Application : marriages in Greece
Further examples and exercises
Interactive time series analysis and forecasting
Installing BATS
Tutorial : introduction to BATS
Tutorial : introduction to modelling
Tutorial : advanced modelling
Tutorial : modelling with incomplete data
Tutorial : data management
BATS reference
Communications
Menu descriptions.
Series
Series
Texts in statistical science ^A1137025 ^A1137025.
Published
New York : Chapman and Hall, c1994.
Language
English
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