Author: Víctor Gómez
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48
Book Description
Program TRAMO "Time Series Regression with ARIMA Noise, Missing Observations, and Outliers" Instructions for the User
Author: Víctor Gómez
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48
Book Description
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48
Book Description
Program TRAMO "Time Series Regression with ARIMA Noise, Missing Observations, and Outliers"
Author: Víctor Gómez
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 31
Book Description
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 31
Book Description
Program TRAMO "Time Series Regression with ARIMA Noise, Missing Observations, and Outliers" instructions for the user
Programs tramo (time series regression with Arima noise, missing observations and outliers) and seats (signal extraction in Arima time series ) instructions for the user (beta version
Program TRAMO Time Series Regression with ARIMA Noise, Missing Obseervations, and Outliers Instructions for the User
Programs TRAMO (Time Series Regression with ARIMA Noise,Missing Observations and Outliers) and SEATS (Signal Extraction in ARIMA Time Series)
Time Series Regression with ARIMA Noise and Missing Observations Program TRAM
Author: Víctor Gómez
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 176
Book Description
Publisher:
ISBN:
Category : Box-Jenkins forecasting
Languages : en
Pages : 176
Book Description
Times Series Regression with Arima Noise and Missing Observations Program Tram
Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
Author: Estela Bee Dagum
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Applied Time Series Analysis
Author: Terence C. Mills
Publisher: Academic Press
ISBN: 0128131179
Category : Business & Economics
Languages : en
Pages : 354
Book Description
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others. Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study Covers both univariate and multivariate techniques in one volume Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples
Publisher: Academic Press
ISBN: 0128131179
Category : Business & Economics
Languages : en
Pages : 354
Book Description
Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others. Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study Covers both univariate and multivariate techniques in one volume Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples