Multiple Time Series Models PDF ePub eBook

Books Info:

Multiple Time Series Models free pdf Many analyses of time series data involve multiple, related variables.a Multiple Time Series Models presents many specification choices and special challenges.a This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression.aaThe text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned.a Specification, estimation, and inference using these modelsais discussed.a The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available.Key FeaturesOffers a detailed comparison of different time series methods and approaches. Includes a self-contained introduction to vector autoregression modeling. Situates multiple time series modeling as a natural extension of commonly taught statistical models.

About Patrick T. Brandt

Patrick T. Brandt is an Assistant Professor of Political Science in the School of Social Science at the University of Texas at Dallas. He has published in the American Journal of Political Science and Political Analysis. He teaches courses in social science research methods and social science statistics. His current research focuses on the development and application of time series models to the study of political institutions, political economy, and international relations. He received an A.B. (1990) in Government from the College of William and Mary, an M.S. (1997) in Mathematical Methods in the Social Sciences from Northwestern University, and a Ph.D. (2001) in Political Science from Indiana University. Before joining the faculty at the University of Texas at Dallas, he held positions at the University of North Texas, Indiana University, and as a fellow at the Harvard-MIT Data Center. John T. Williams was Professor and Chair of the Department of Political Science at University of California, Riverside. He taught time series analysis at the Inter-university Consortium for Political and Social Research Summer Training Program for over ten years. His work uses statistical methods in the study of political economy and public policy. He co-authored two books: Compound Dilemmas: Democracy, Collective Action, and Superpower Rivalry (University of Michigan Press, 2001) and Public Policy Analysis: A Political Economy Approach (Houghton Mifflin, 2000). He published over twenty journal articles and book chapters on a wide range of topics, ranging from macroeconomic policy to defense spending to forest resource management. He was a leader in the application of new methods of statistical analysis to political science, especially the use of vector autoregression (VAR), Bayesian, and event count time series models. He received a B.A. (1979), an M.A. (1981) from North Texas State University, and a Ph.D. (1987) from the University of Minnesota. Before moving to Riverside in 2001, he held academic positions at the University of Illinois Chicago (1985-1990) and at Indiana University, Bloomington (1990-2001).

Details Book

Author : Patrick T. Brandt
Publisher : SAGE Publications Inc
Data Published : 02 November 2006
ISBN : 1412906563
EAN : 9781412906562
Format Book : PDF, Epub, DOCx, TXT
Number of Pages : 120 pages
Age + : 18 years
Language : English
Rating :

Reviews Multiple Time Series Models

17 Comments Add a comment

Related eBooks Download

  • Time Series Analysis free pdfTime Series Analysis

    Time Series Analysis With Applications in R. Second Edition. presents an accessible approach to understanding time series models and their applications. Although the emphasis is on time domain ARIMA models and their analysis..

  • Jmp 12 Specialized Models free pdfJmp 12 Specialized Models

    JMP 12 Specialized Models provides details about modeling techniques such as partitioning. neural networks. nonlinear regression. and time series analysis. Topics include the Gaussian platform..

  • Predictions in Time Series Using Regression Models free pdfPredictions in Time Series Using Regression Models

    This book deals with the statistical analysis of time series and covers situations that do not fit into the framework of stationary time series. as described in classic books by Box and Jenkins. Brockwell and Davis and others..

  • Age-period-cohort Models free pdfAge-period-cohort Models

    Develop a Deep Understanding of the Statistical Issues of APC Analysis Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age..

  • Fixed Effects Regression Models free pdfFixed Effects Regression Models

    This book will show how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models. logistic models. Poisson models. Cox regression models..

  • Multiple Time Series Models free pdfMultiple Time Series Models

    Reading Free Online. Many analyses of time series data involve multiple, related variables.a Multiple Time Series Models presents many specification choices and special challenges.a This book reviews