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 ...

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 ...

Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician (CMT). Gordon Scott has been an active investor and technical analyst or 20+ years. He ...