In this thesis, the problem of point estimator of parameter vector in two states with and without restriction in the family of elliptical distributions with classical, Bayesian and Bayesian wavelet approaches is discussed.
In the classical and Bayesian sense, a variety of balance loss functions are used to obtain the shrinkage estimators.
It has also been investigated by finding the generalized Bayes estimator and introducing the generalized Bayesian Soft threshold wavelet estimator, minimaxity and admissibility of this estimator. Also, the Stein unbiased risk estimator threshold in the family of elliptical distributions under balance loss function is also obtained. Finally, all the theoretical results are studied using simulation study and real example in practice.