Chapter 40 : Multivariate autoregressive models
نویسنده
چکیده
منابع مشابه
Chapter on Bayesian Inference for Stochastic Volatility Modeling
This chapter reviews the major contributions over the last two decades to the literature on the Bayesian analysis of stochastic volatility (SV) models (univariate and multivariate). Bayesian inference is performed by tailoring Markov chain Monte Carlo (MCMC) or sequential Monte Carlo (SMC) schemes that take into account the specific modeling characteristics. The popular univariate stochastic vo...
متن کاملDynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models
Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the exibility of univariate GARCH models coupled with parsimonious parametric models for the c...
متن کاملMultivariate Fault Detection using Vector Autoregressive Moving Average and Orthogonal Transformation in Residual Space
We propose the use of multivariate orthogonal space transformations and Vector Autoregressive Moving-Average (VARMA) models in combination with data-driven system identification models to improve residual-based approaches to fault detection in rolling mills. Introducing VARMA models allows us to build k-step ahead multi-dimensional prediction models including the time lags that best explain the...
متن کاملForecasting with Periodic Autoregressive Time Series Models
This chapter is concerned with forecasting univariate seasonal time series data using periodic autoregressive models We show how one should account for unit roots and deterministic terms when generating out of sample forecasts We illus trate the models for various quarterly UK consumption series This is the rst version July of a chapter that is to be prepared for potential inclusion in the Comp...
متن کاملForecasting Exchange Rates for Central and Eastern European Currencies: A Comparison of Multivariate Time Series Models Jes
This article compares the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian vector error correction (BVEC) models in forecasting the exchange rates for ve Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Polish Zloty, Slovak Koruna and Slovenian Tolar) agains...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006