Generalized Autoregressive Score Models in R: The GAS Package
Journal of Statistical Software, Vol. 88, Issue 6, pp. 1-28, 2019
28 Pages Posted: 21 Aug 2016 Last revised: 4 Feb 2019
Date Written: August 17, 2016
Abstract
This paper presents the R package GAS for the analysis of time series under the Generalized Autoregressive Score (GAS) framework of Creal et al. (2013) and Harvey (2013). The distinctive feature of the GAS approach is the use of the score function as the driver of time{variation in the parameters of nonlinear models. The GAS package provides functions to simulate univariate and multivariate GAS processes, estimate the GAS parameters and to make time series forecasts. We illustrate the use of the GAS package with a detailed case study on estimating the time-varying conditional densities of a set of financial assets.
Keywords: GAS, Time Series Models, Score Models, Dynamic Conditional Score, R Software
JEL Classification: C01, C22, C32, C53
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