Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The transformation of credit scores into probabilities of default plays an important role in credit risk estimation. The linear logistic regression has developed into a standard calibration approach ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Rosineide F. da Paz, Narayanaswamy Balakrishnan, Jorge Luis Bazán, L-Logistic regression models, Brazilian Journal of Probability and Statistics, Vol. 33, No. 3 (2019), pp. 455-479 ...

The CATMOD procedure can perform linear regression and logistic regression of response functions for data that can be represented in a contingency table. See Chapter 5, "Introduction to Categorical ...

Qualitative Dependent Variables and Logistic Regression The LOGISTIC procedure in SAS/STAT software fits linear logistic regression models for binary or ordinal response data by the method of maximum ...