Shrinkage Estimation Theory for Unbiased Estimators of Dependent Observations

2016 Fiscal Year Final Research Report

• Project/Area Number: 26540015
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Statistical science
• Research Institution: Waseda University
• Principal Investigator: Taniguchi Masanobu 早稲田大学, 理工学術院, 教授 (00116625)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 縮小推定量 / 最尤推定量 / 曲確率モデル / ポートフォリオ推測 / 金融時系列モデル / 非線形時系列モデル

Outline of Final Research Achievements

Introducing a curved probability model,which includes a class of very general nonlinear time series models,we proposed a shrinkage estimator for unknown parameter of the curved probability models. Then we developed the third-order asymptotic estimation theory for the estimator, and provided a sufficient condition for the shrinkage estimator to improve the usualestimators. The results can be applied to the problem of portfolio coefficient estimation. Because the results are very general, we can apply them to a variety of statistical observations generated by multivariate financial time series, multivariate time series regression models and usual mulitivariate models.

Free Research Field

統計科学分野