Estimators for the parameters of autoregressive time series are compared, emphasizing processes with a unit root or a root close to 1. The approximate bias of the sum of the autoregressive ...

Two methods of parameter estimation for a general nonlinear autoregressive process with beta-ARCH innovations are discussed and the large sample properties of the estimators for each method are ...

Autoregressive models are a statistical technique used to predict future values in a sequence based on its past values. It is essentially a fancy way of saying that it uses the past to predict the ...

Integer-valued time series analysis is a rapidly evolving field that focuses on the statistical modelling and forecasting of discrete data, such as counts of events over time. This area of research is ...

Researchers combined two types of generative AI models, an autoregressive model and a diffusion model, to create a tool that leverages the best of each model to rapidly generate high-quality images.