Introduction to Multiple Time Series Analysis
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The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book.
- Introduction to Multiple Time Series Analysis - Helmut Lütkepohl - Google книги.
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Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Inhaltsverzeichnis 1. Finite Order Vector Autoregressive Processes. Stable Vector Autoregressive Processes. Estimation of Vector Autoregressive Processes. Infinite Order Vector Autoregressive Processes. Vector Autoregressive Moving Average Processes. Systems with Exogenous Variables and Nonstationary Processes. Systems of Dynamic Simultaneous Equations. Nonstationary Systems with Integrated and Cointegrated Variables.
State Space Models. Like its predecessor, this book provides the most complete coverage of stationary vector autoregressive VAR and vector autoregressive moving average VARMA models of any book. Written in a clear, building-block style, the book begins with first principles and neatly adds pieces to the foundation as needed.
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