Overview Regression explains how changes in one factor influence another with clarity.Each regression type is suited for ...

Objectives This study uses nationally representative survey data from the USA to estimate the relationship between a history of heart attack or stroke with the prevalence of mental health symptoms.

Primary and secondary outcome measures The primary outcome was tracheal injury score, assessed via fibreoptic bronchoscopy for hyperaemia, ischaemia, ulcers and perforation. Lesions were classified as ...

The core of big data models lies in the synergy of algorithm innovation, computational power support, and data governance to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

Abstract: We analyze the statistical properties of slope estimates obtained from linear regression with sample-minimum Erlang variates. The sample-minimum of sequential blocks has the effect of ...

This article considers the problem of inference for nested least squares averaging estimators. We study the asymptotic behavior of the Mallows model averaging estimator (MMA; Hansen, 2007) and the ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Attention-based architectures are a powerful force in modern AI. In particular, the emergence of in-context learning abilities enables task generalization far beyond the original next-token prediction ...

Ask ten gamers about their keyboard switch preferences, and you'll likely spark a debate that rivals console wars. The divide between linear and clicky switches runs deep in gaming circles, with each ...

The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

There are surveys that gather precise information on an outcome of interest, but measure continuous covariates by a discrete number of intervals, in which case the covariates are interval censored.