Author: Ding-Hwa Lei
Publisher:
ISBN:
Category : Prediction theory
Languages : en
Pages : 90
Book Description
Introduction to Univariate Box-Jenkins Forecasting Procedure
Author: Ding-Hwa Lei
Publisher:
ISBN:
Category : Prediction theory
Languages : en
Pages : 90
Book Description
Publisher:
ISBN:
Category : Prediction theory
Languages : en
Pages : 90
Book Description
Forecasting with Univariate Box - Jenkins Models
Author: Alan Pankratz
Publisher: John Wiley & Sons
ISBN: 0470317272
Category : Mathematics
Languages : en
Pages : 576
Book Description
Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.
Publisher: John Wiley & Sons
ISBN: 0470317272
Category : Mathematics
Languages : en
Pages : 576
Book Description
Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.
Short Term Forecasting
Author: Thomas M. O'Donovan
Publisher: John Wiley & Sons
ISBN:
Category : Business & Economics
Languages : en
Pages : 322
Book Description
Publisher: John Wiley & Sons
ISBN:
Category : Business & Economics
Languages : en
Pages : 322
Book Description
A Practical Guide to Box-Jenkins Forecasting
Author: John C. Hoff
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 344
Book Description
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 344
Book Description
The Development of a Forecasting Model for Weiser Inc. Using the Univariate Box-Jenkins Method
Author: Alan M. Marchant
Publisher:
ISBN:
Category : Locks and keys
Languages : en
Pages : 176
Book Description
Publisher:
ISBN:
Category : Locks and keys
Languages : en
Pages : 176
Book Description
An Introduction to Short Term Forecasting Using the Box-Jenkins Methodology
Author: Vincent A. Mabert
Publisher:
ISBN:
Category : Social Science
Languages : en
Pages : 68
Book Description
Publisher:
ISBN:
Category : Social Science
Languages : en
Pages : 68
Book Description
Introduction to the Box-Jenkins Technique of Forecasting
Author: National CSS, Inc
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages :
Book Description
Box-Jenkins in Practice
Author: Gordon McLeod
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 444
Book Description
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 444
Book Description
Using GENSTAT for Univariate Box-Jenkins Forecasting
Author: Marthinus Christoffel Koen
Publisher:
ISBN: 9780799211351
Category : Forecasting
Languages : en
Pages : 46
Book Description
Publisher:
ISBN: 9780799211351
Category : Forecasting
Languages : en
Pages : 46
Book Description
Introduction to Time Series and Forecasting
Author: Peter J. Brockwell
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429
Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429
Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.