<div class="cnt" id="blog_text"><font color="#ff0000">Analysis of Integrated and Co-integrated Time Series with R (Use R) </font><br/>&nbsp;&nbsp;<br/><span class="item_label">by</span><br/>&nbsp;&nbsp;<strong>Bernhard Pfaff </strong><br/><br/><ul><li><strong>Publisher:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Springer</li><li><strong>Number Of Pages:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 208</li><li><strong>Publication Date:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 2008-08-11</li><li><strong>ISBN-10 / ASIN:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 0387759662</li><li><strong>ISBN-13 / EAN:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 9780387759661</li><li><strong>Binding:</strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Paperback</li></ul><br/><p>The analysis of integrated and co-integrated time series can be<br/>considered as the main methodology employed in applied econometrics.<br/>This book not only introduces the reader to this topic but enables him<br/>to conduct the various unit root tests and co-integration methods on<br/>his own by utilizing the free statistical programming environment R.<br/>The book encompasses seasonal unit roots, fractional integration,<br/>coping with structural breaks, and multivariate time series models. The<br/>book is enriched by numerous programming examples to artificial and<br/>real data so that it is ideally suited as an accompanying text book to<br/>computer lab classes.</p><p>The second edition adds a discussion of vector auto-regressive,<br/>structural vector auto-regressive, and structural vector<br/>error-correction models. To analyze the interactions between the<br/>investigated variables, further impulse response function and forecast<br/>error variance decompositions are introduced as well as forecasting.<br/>The author explains how these model types relate to each other.</p><p><a href="http://www.namipan.com/d/e09f42033dafac760dc84e95e49a090cd301f44ce4dd1600" target="_blank">纳米盘下载</a>|<a href="http://ifile.it/l7w6ixz" target="_blank">Ifile</a></p></div>
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