We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the ...

We study maximum likelihood estimation in log-linear models under conditional Poisson sampling schemes. We derive necessary and sufficient conditions for existence of the maximum likelihood estimator ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

Although the world in which we live in is non-linear, or multi-dimensional, engineers and scientists have long used linear mathematical formulas to create models to predict physical phenomena such as ...

The artificial intelligence major is an interdisciplinary field that integrates knowledge from multiple disciplines. To excel ...

OpenAI Unveils ‘Strawberry’ Model, Optimized for Complex Coding and Math Your email has been sent OpenAI o1, one of a family of models known as Strawberry, is designed for building rather than ...