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The subject is covered in sufficient depth for a comprehensive introduction with reading lists after each chapter for those interested in further detail
consultants and postgraduates
New Introduction to Multiple Time Series Analysis Universidad Panamericana Guadalajara Featuring a newThis reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated, vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models.
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