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 ...

Tesla’s Full Self-Driving system relies on autoregressive transformers to predict and navigate complex driving scenarios.

The Canadian Journal of Statistics / La Revue Canadienne de Statistique Threshold autoregressive models are widely used in time-series applications. When building or using such a model, it is ...

The autoregressive spectral estimator exhibits errors when the time series contains a transient spectral component. A variation in the choice of the autoregressive parameters minimizes these errors.

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...

To capture the "long-memory" effect in volatility, a multiplicative component conditional autoregressive range (MCCARR) model is proposed. We show theoretically that the MCCARR model can capture the ...