Analysis of Integrated and Co-Integrated Time Series with R: Use R!

"All in all, it is a book by which the usage of R for analyzing time series with the mentioned tools will surely be inhanced. It is hoped that the series expands further with similar well done texts." Allgemeines Statistisches Archive, vol. 90, No. 3, pgs 486-487 From the reviews: a oeAll in all, it is a book by which the usage of R for analyzing time series with the mentioned tools will surely be inhanced. It is hoped that the series expands further with similar well done texts.a (Allgemeines Statistisches Archiv, 90: 3, pgs 486-487) a oeTopics in stationary and non-stationary time series, together with their application to univariate and multivariate analyses are covered in this book. a ] The author explains how easily the methods and tools can be implemented in R a" the open-source statistical programming environment. Exercises are provided a ] and give the reader an opportunity to apply the presented tests and methods to previously published data sets. The text is suitable for private study but would provide an excellent course companion to computer-based laboratory classes.a (C.M. Oa (TM)Brien, Short Book Reviews, 26: 2, 2006) a oeI would recommend this book as a handy reference. It tersely presents the basic ideas in integrated or cointegrated analysis of time series and provides easily understandable examples of R code in implementing those examples.a (Jane L. Harvill, Journal of the American Statistical Association, 102: 477, 2007) a oeA welcome addition a" both for econometricians and non-econometricians a" as it stimulates creative research in disciplines outside economics and sharing of code in this area through the CRAN project. a ] Some examples with real data are also presented. a ] The exercises are more applied a ] and use interesting data sets. The bibliography is very useful. a ] I highly recommend this book.a (Juana Sanchez, Journal of Applied Statistics, 34: 8, 2007) From the reviews: "All in all, it is a book by which the usage of R for analyzing time series with the mentioned tools will surely be inhanced. It is hoped that the series expands further with similar well done texts." Allgemeines Statistisches Archiv, Vol. 90, No. 3, pgs 486-487 "Topics in stationary and non-stationary time series, together with their application to univariate and multivariate analyses are covered in this book. a ] The author explains how easily the methods and tools can be implemented in R a" the open-source statistical programming environment. Exercises are provided a ] and give the reader an opportunity to apply the presented tests and methods to previously published data sets. The text is suitable for private study but would provide an excellent course companion to computer-based laboratory classes." (C. M. Oa (TM)Brien, Short Book Reviews, Vol. 26 (2), 2006) "I would recommend this book as a handy reference. It tersely presents the basic ideas in integrated or cointegrated analysis of time series and provides easily understandable examples of R code in implementing those examples." (Jane L. Harvill, Journal of the American Statistical Association, Vol. 102, No. 477, 2007) "A welcome addition a" both for econometricians and non-econometricians a" as it stimulates creative research in disciplines outside economics and sharing of code in this area through the CRAN project. a ] Some examples with real data are also presented. a ] The exercises are more applied a ] and use interesting data sets. The bibliography is very useful. a ] I highly recommend this book." (Juana Sanchez, Journal of Applied Statistics, Vol. 34 (8), 2007) From the reviews: "All in all, it is a book by which the usage of R for analyzing time series with the mentioned tools will surely be inhanced. It is hoped that the series expands further with similar well done texts." Allgemeines Statistisches Archiv, Vol. 90, No. 3, pgs 486-487 "Topics in stationary and non-stationary time series, together with their application to univariate and multivariate analyses are covered in this book. ??? The author explains how easily the methods and tools can be implemented in R ??? the open-source statistical programming environment. Exercises are provided ??? and give the reader an opportunity to apply the presented tests and methods to previously published data sets. The text is suitable for private study but would provide an excellent course companion to computer-based laboratory classes." (C. M. O???Brien, Short Book Reviews, Vol. 26 (2), 2006) "I would recommend this book as a handy reference. It tersely presents the basic ideas in integrated or cointegrated analysis of time series and provides easily understandable examples of R code in implementing those examples." (Jane L. Harvill, Journal of the American Statistical Association, Vol. 102, No. 477, 2007)