Sankhyā: The Indian Journal of Statistics, Series B (2008-), Vol. 74, No. 1 (May 2012), pp. 107-125 (19 pages) We develop objective Bayesian analysis for the linear regression model with random errors ...

Linear regression can be done under the two schools of statistics (frequentist and Bayesian) with some important differences. Briefly, frequentist statistics relies on repeated sampling and ...

We’ll use the R software language to run some examples of multiple linear regression and probit regression using the bayesm package that will illustrate these concepts. Hopefully you'll come away with ...

We propose Bayesian parametric and semiparametric partially linear regression methods to analyze the outcome-dependent follow-up data when the random time of a follow-up measurement of an individual ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.