Theory and application of a Bayesian information criterion
Project/Area Number |
24740069
|
Research Category |
Grant-in-Aid for Young Scientists (B)
|
Allocation Type | Multi-year Fund |
Research Field |
General mathematics (including Probability theory/Statistical mathematics)
|
Research Institution | Takasaki City University of Economics |
Principal Investigator |
Miyata Yoichi 高崎経済大学, 経済学部, 准教授 (10514250)
|
Project Period (FY) |
2012-04-01 – 2016-03-31
|
Project Status |
Completed (Fiscal Year 2015)
|
Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
|
Keywords | ラプラス近似 / ベイズ統計学 / 情報量規準 / 統計的漸近理論 / 漸近理論 |
Outline of Final Research Achievements |
When applying Laplace's method to approximate an integral, we require an exact mode of its integrand. We derive a Laplace approximation using an asymptotic mode of an asymptotic mode instead of the exact mode, and present some ways to establish asymptotic modes with a desirable order. The class of the asymptotic modes is wide and includes consistent estimators with some convergence rate and a true parameter.
|
Report
(5 results)
Research Products
(10 results)