Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

本文将详细解读NeurIPS 2024最佳论文："Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction（视觉自回归建模：基于下一尺度预测的可扩展图像生成）"。 该论文提出了视觉自回归建模（Visual Autoregressive ...

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 ...

Learn how CALM uses continuous vectors to bypass the token bottleneck and cut AI compute by up to 40%. Continuous ...

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 ...

This article introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroscedasticity (BAR-GARCH). The proposed model, as an extension of the BAR ...

Artificial intelligence has reached a point where it can compose text that sounds so human that it dupes most people into thinking it was written by another person. These AI programs—based on what are ...

Every time a language model like GPT-4, Claude or Mistral generates a sentence, it does something deceptively simple: It picks one word at a time. This word-by-word approach is what gives ...

This section briefly introduces the forecasting methods used by the FORECAST procedure. Refer to textbooks on forecasting and see "Forecasting Methods" later in this chapter for more detailed ...