Linear regression models the relationship between a dependent and independent variable(s). A linear regression essentially estimates a line of best fit among all variables in the model. Regression ...

Researchers have explained how large language models like GPT-3 are able to learn new tasks without updating their parameters, despite not being trained to perform those tasks. They found that these ...

Agriculture is one of the largest contributors to global greenhouse gas emissions, releasing carbon dioxide, methane, and nitrous oxide through fertilizer use, livestock production, irrigation, and ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

We consider marked empirical processes indexed by a randomly projected functional covariate to construct goodness-of-fit tests for the functional linear model with scalar response. The test statistics ...

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 ...

In a thermally linear system, superposition may be applied to predict the transient response of the system to step changes in input power. This article is the second in a two-part series. Part one of ...