Continuous-Time Autoregressive Moving Average (CARMA) processes extend the classical discrete-time ARMA framework to continuous time, offering a flexible modelling approach for phenomena where ...

A class of first-order autoregressive processes is given for which the extreme value limit theorems of Loynes and Leadbetter do not apply. A limit theorem is derived ...

Estimates of the parameters in normal autoregressive (AR(p)) processes may be obtained as functions of certain runs and subsequences in the associated clipped 0 - 1 processes. For example, the ...

After computing the sample autocovariance matrices, PROC STATESPACE fits a sequence of vector autoregressive models. These preliminary autoregressive models are used to estimate the autoregressive ...

A model with first-order autoregressive errors, AR(1), has the form while an AR(2) error process has the form and so forth for higher-order processes. Note that the ...

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.