A Sequential Shrinkage Estimating Method for Tobit Regression Model ()
ABSTRACT
In the applications of Tobit regression models we always encounter the
data sets which contain too many variables that only a few of them contribute
to the model. Therefore, it will waste much more samples to estimate the “non-effective”
variables in the inference. In this paper, we use a sequential procedure for
constructing the fixed size confidence set for the “effective” parameters to
the model by using an adaptive shrinkage estimate such that the “effective”
coefficients can be efficiently identified with the minimum sample size based
on Tobit regression model. Fixed design is considered for numerical simulation.
Share and Cite:
Lu, H. , Dong, C. and Zhou, J. (2021) A Sequential Shrinkage Estimating Method for Tobit Regression Model.
Open Journal of Modelling and Simulation,
9, 275-280. doi:
10.4236/ojmsi.2021.93018.
Cited by
No relevant information.