This 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. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis.
Payment & Security
Su información de pago se procesa de forma segura. No almacenamos los detalles de la tarjeta de crédito ni tenemos acceso a la información de su tarjeta de crédito.
Chat-en-linea, Whatsapp, Teléfono y Correo Electrónico