In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

This short course provides an introduction to regression analysis, a commonly used method to study the relationship between a response variable and one or more explanatory variables. The course will ...

This is a preview. Log in through your library . Abstract Scientists may wish to analyze correlated outcome data with constraints among the responses. For example, piecewise linear regression in a ...

STRI copy 39088014660302 purchased with funds from the S. Dillon Ripley Endowment. SERC copy 39088016914160 purchased with funds from the S. Dillon Ripley Endowment ...

We propose an additive hazards model with latent variables to investigate the observed and latent risk factors of the failure time of interest. Each latent risk factor is characterized by correlated ...