Variable selection in joint mean and variance models

In many applications,particularly in the econometric area and industrial quality improvement experiments,there is a great need to model the variance.A unified procedure was proposed to simultaneously select significant variables in joint mean and variance models which provide a useful extension of the classical normal regression models.It is further shown that the presented penalized estimator enjoys the consistency and the oracle property.Simulation and practice show that this model and method are useful and effective.