Separate binary regression models When the dependent variable is ordinal, such as here, we can choose to dichotomise it and use binary logistic regression. A variable with three categories can be ...

The benefits of regression analysis are manifold: The regression method of forecasting is used for, as the name implies, forecasting and finding the causal relationship between variables.

The Green Bay Packers made a major decision on Monday, releasing veteran cornerback Jaire Alexander—once a key piece of their defense when healthy. The move removes a potential distraction from ...

Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical logistic ...

In this paper we consider high-dimensional multiclass classification by sparse multinomial logistic regression. We propose first a feature selection procedure based on penalized maximum likelihood ...

What Are Autoregressive Models? Autoregressive models are statistical models used for time series analysis, where current values are predicted based on a linear combination of past values. These ...

Objectives To investigate factors influencing the effectiveness of intensive sound masking therapy on tinnitus using logistic regression analysis. Design The study used a retrospective cross-section ...

Excess returns are returns achieved that are more significant than the return of a proxy. Excess returns will depend on a designated investment return comparison for analysis.

In a seminal paper Abadie et al (2010) develop the synthetic control procedure for estimating the effect of a treatment, in the presence of a single treated unit and a number of control units, with ...

This project uses the Kaggle competition dataset from the "ML with Python Course Project" to predict campus recruitment outcomes. It includes preprocessing, EDA, feature engineering, and model ...