Do Large Language Models (Really) Need Statistical Foundations? Dr. Linglong Kong is a Professor in the Department of ...

BACKGROUND The application of geographically weighted regression (GWR) – a local spatial statistical technique used to test for spatial nonstationarity – has grown rapidly in the social, health, and ...

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

In this short course we will provide an introduction to linear regression and how to utilize it in R. We will cover the theory of linear regression as well as demonstrating how to use R to make and ...

This is a preview. Log in through your library . Abstract Nonlinear regression models are commonly used in toxicology and pharmacology. When fitting nonlinear models ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...