gasmodel: An R Package for Generalized Autoregressive Score Models

TL;DR

The paper introduces the gasmodel R package, enabling users to efficiently estimate, forecast, and simulate diverse GAS models with flexible distribution choices and exogenous variable integration.

Contribution

It provides a comprehensive software tool for GAS models, supporting various distributions, dynamics, and exogenous variables, facilitating broader application and research.

Findings

Supports a wide range of distributions

Enables flexible model specification

Facilitates estimation, forecasting, and simulation

Abstract

Generalized autoregressive score (GAS) models are a class of observation-driven time series models that employ the score to dynamically update time-varying parameters of the underlying probability distribution. GAS models have been extensively studied and numerous variants have been proposed in the literature to accommodate diverse data types and probability distributions. This paper introduces the gasmodel package, which has been designed to facilitate the estimation, forecasting, and simulation of a wide range of GAS models. The package provides a rich selection of distributions, offers flexible options for specifying dynamics, and allows to incorporate exogenous variables. Model estimation utilizes the maximum likelihood method.