JSTOR Daily

Bayesian Variable Selection for High Dimensional Generalized Linear Models: Convergence Rates of the Fitted Densities

Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...
JSTOR Daily

Some Bayesian Inferences for a Changing Linear Model

This paper is a generalization of earlier studies by Ferreira (1975) and Holbert and Broemeling (1977), who used improper prior distributions in order to make informal Bayesian inferences for the ...
Business Wire

'Linear Models in Statistics 2nd Edition' is the Essential Introduction to the Theory and Application of Linear Models

DUBLIN, Ireland--(BUSINESS WIRE)--Research and Markets (http://www.researchandmarkets.com/reports/c81986) has announced the addition of “Linear Models in Statistics ...
technologynetworks

Linear Regression

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...