Il giorno martedì 4 ottobre alle ore 15.00 presso la Aula Seminari al IV piano dell’edificio U7, il prof. Masanobu Taniguchi della Waseda University di Tokyo terrà un seminario su
High Order Asymptotic Theory of Shrinkage Estimation for General Statistical Models
In this paper we develop the high order asymptotic theory of shrinkage estimators for general statistical models, which include dependent processes, multivariate models and regression models, i.e., non-i.i.d. models.
Introducing a shrinkage estimator of MLE, we compare it with that of MLE by third-order mean squares error (MSE).
A sufficient condition for the shrinkage estimator to improve the MLE will be given in a very general fashion.
Our model is described as a curved statistical model p(·;\theta(u)), where \theta is a parameter of larger model and u is a parameter of interest with dim u < dim \theta.
This setting is especially suitable for estimation of portfolio coefficients u based on mean and variance parameters \theta.
We also mention the advantage of our shrinkage estimators when the dimension of parameter becomes large.
Numerical studies are given, and illuminate an interesting feature of the shrinkage estimator. (joint work with: Hiroshi SHIRAISHI, Yoshihiro SUTO, Takashi YAMASHITA)