| 期刊全稱 | Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series | | 影響因子2023 | Estela Bee Dagum,Pierre A. Cholette | | 視頻video | http://file.papertrans.cn/184/183394/183394.mp4 | | 發(fā)行地址 | First statistical book to systematically deal with these time series data transformations | | 學(xué)科分類 | Lecture Notes in Statistics | | 圖書封面 |  | | 影響因子 | .In modern economies, time series play a crucial role at all levels of activity. They are used by decision makers to plan for a better future, by governments to promote prosperity, by central banks to control inflation, by unions to bargain for higher wages, by hospital, school boards, manufacturers, builders, transportation companies, and by consumers in general...A common misconception is that time series data originate from the direct and straightforward compilations of survey data, censuses, and administrative records. On the contrary, before publication time series are subject to statistical adjustments intended to facilitate analysis, increase efficiency, reduce bias, replace missing values, correct errors, and satisfy cross-sectional additivity constraints. Some of the most common adjustments are benchmarking, interpolation, temporal distribution, calendarization, and reconciliation...This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. | | Pindex | Book 2006 |
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