This is a preview. Log in through your library . Abstract Students in statistics or data science usually learn early on that when the sample size n is large relative to the number of variables p, ...

Maximum likelihood estimates in problems in which the likelihood is smooth and the parameter space is defined by linear or smooth nonlinear inequality constraints can be obtained using available ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

This is the eighth in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...