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I present the 'gasmodel' package, designed to facilitate the estimation, forecasting, and simulation of a broad range of generalized autoregressive score (GAS) models. 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. The package supports diverse data types, offers a rich selection of distributions, provides flexible options for specifying dynamics, and allows for the incorporation of exogenous variables.