Template for editors of a "contributed volume", provided by Springer, to help structure the manuscript, e.g., define the heading hierarchy. Predefined style formats are available for all the necessary structures that are supposed to be part of the manuscript.
The original template has been modified so that contribution from each author can be contained in their own folders, using the import package.
Note: These templates are not intended for the preparation of the final page layout! The final layout will be created by Springer according to their layout specifications.
This template satisfies the formatting requirements for Masters and Doctoral theses and dissertations from the College of Graduate Studies at the University of Idaho. It's easy to use and allows you to write each chapter as a separate tex document.
Estilo Beamer para uso com o pacote Beamer. Esta versão está atualizada conforme as orientações do período de silêncio eleitoral de 2022 e deverá ser utilizada até o final do referido período eleitoral.
Linear regression is one of the most widely used statistical methods available today. It is used by data analysts and students in almost every discipline. However, for the standard ordinary least squares method, there are several strong assumptions made about data that is often not true in real world data sets. This can cause numerous problems in the least squares model. One of the most common issues is a model overfitting the data. Ridge Regression and LASSO are two methods used to create a better and more accurate model. I will discuss how overfitting arises in least squares models and the reasoning for using Ridge Regression and LASSO include analysis of real world example data and compare these methods with OLS and each other to further infer the benefits and drawbacks of each method.
Chris Van Dusen