The company’s Designer platform provides a linear regression tool to create simple models for estimating values or evaluating relationships between variables based on their linear correlations.

Linear forecasting models can be used in both types of forecasting methods. In the case of causal methods, the causal model may consist of a linear regression with several explanatory variables.

We consider the problem of accounting for model uncertainty in linear regression models. Conditioning on a single selected model ignores model uncertainty, and thus leads to the underestimation of ...

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, ...

Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, Professional Master’s Degree in Applied Mathematics Prior knowledge needed: Basic calculus ...

Wayne A. Fuller, J. N. K. Rao, Estimation for a Linear Regression Model with Unknown Diagonal Covariance Matrix, The Annals of Statistics, Vol. 6, No. 5 (Sep., 1978 ...