Tid: 6 september 2017, kl 13-14
Plats: B705


Multicollinearity, which is known as the linear dependency between the explanatory variables, has serious problems in the estimation of the regression parameters. Therefore, several biased estimation methods were proposed to overcome the multicollinearity problem in linear regression and some authors carry some biased estimation ideas over to other regression models such as generalized linear regression and linear mixed models. In this talk, I am going to introduce some biased estimation methods in linear regression model and their extensions to other regression models.