Statistical Methodology for Stabilizing Grouped Data Analysis
| Project/Area Number |
18K12757
|
|---|
| Research Category |
Grant-in-Aid for Early-Career Scientists
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
Basic Section 07030:Economic statistics-related
|
|---|
| Research Institution | The University of Tokyo |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2018-04-01 – 2021-03-31
|
| Project Status |
Completed (Fiscal Year 2020)
|
| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
|
|---|
| Keywords | 統計モデリング / ロバスト統計 / 空間統計 / 階層モデル / 異質性 / ベイズ統計 / 混合効果モデル / グループデータ / 個体差 / 地域差 |
|---|
| Outline of Final Research Achievements |
Data in the form of groupings based on attributes such as individuals and regions are called group data, and are frequently used in various scientific fields. In this study, we focused on the problems of the existing statistical analysis methods for such data, especially the limitation of model flexibility, computational cost for large-scale data, and robustness in the presence of outliers, and developed several effective methods to solve them. We also revealed some theoretical properties of the developed methods.
|
| Academic Significance and Societal Importance of the Research Achievements |
本研究成果によってグループデータの分析において障壁となっていた応用上の問題点に対して、いくつかの効果的な解決策を提示することができた。提案した手法の多くは実装したコードをオープンソースとして公開しており、グループデータを扱う関連分野の研究者や実務家が提案した方法を利用することで、これまでよりも効果的な統計分析を実行することが可能になると考えられる。
|
Report
(4 results)
Research Products
(44 results)
