Here’s what the neolabs are building and why their approaches could unlock new opportunities and cost structures for startups ...

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 ...

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 ...

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 ...

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 model assumed is first-order autoregressive with contemporaneous correlation between cross sections. In this model, the covariance matrix for the vector of random errors u can be expressed as A ...

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 ...

This article develops a novel test for a unit root in general transitional autoregressive models, which is based on the infimum of t-ratios for the coefficient of a parametrized transition function.

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 ...