Dynamic Score-Driven Models, An R Package with Applications - Holý, Vladimír (2025)
Score-driven models are a class of time series models that leverage the score, i.e. the gradient of the log-likelihood function, to iteratively update time-varying parameters of the underlying probability distribution. This thesis comprises seven papers devoted to score-driven models. The first paper introduces an R package called gasmodel, which is designed to facilitate the estimation, forecasting, and simulation of a wide range of score-driven models. The remaining papers focus on the development of specific score-driven models within the fields of sport statistics, operations research, and finance.