Stochastic Parameter Regression Models

Newbold, Paul and Theodore Bos

ISBN 10: 0803924259 / ISBN 13: 9780803924253

Editore: Sage Publications, Beverley Hills and London, 1985

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First edition, first printing. Paperback as issued. 80 pp. Very Good+ condition. No inscriptions.

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Dati bibliografici

• Titolo: Stochastic Parameter Regression Models
• Editore: Sage Publications, Beverley Hills and London
• Data di pubblicazione: 1985
• Lingua: Inglese
• ISBN 10: 0803924259
• ISBN 13: 9780803924253
• Rilegatura: Soft cover
• Edizione: 1st Edition
• Condizione: Very Good+
• Cataloghi dei venditori:
  • Lighter Books
  • Mathematics and Business Studies

Descrizione articolo

Riassunto

This excellent introduction to stochastic parameter regression models is more advanced and technically difficult than other papers in this series. These models allow relationships to vary through time, rather than requiring them to be fixed, without forcing the analyst to specify and analyze the causes of the time-varying relationships. This volume will be most useful to those with a good working knowledge of standard regression models and who wish to understand methods which deal with relationships that vary slowly over time, but for which the exact causes of variation cannot be identified.

Informazioni sull?autore

Paul Newbold was born in England in 1945. In 1966 he obtained a BSc in Economics at the London School of Economics, before continuing to study for a PhD in Statistics at the University of Wisconsin. He worked under the supervision of George Box, and was awarded his PhD in 1970. His first academic posts were at the University of Nottingham, where he spent time in both the Department of Economics and the Department of Mathematics. From 1979-1994 he was Professor at the University of Illinois, before returning to the University of Nottingham in 1994 as Professor of Econometrics. Paul Newbold has had a large influence on the discipline of time series econometrics, particularly in the areas of non-stationary time series, forecasting, and univariate time series analysis. He has published extensively in journals such as Journal of Econometrics, Journal of Business and Economic Statistics, Journal of the American Statistical Association, Biometrika, and Econometric Theory. He retired in 2006 and is now Emeritus Professor of Econometrics.