Statistical Data Fusion for Advanced Use of Multi-source Datasets
Finished by March 31, 2012
![English](../../../image/english-2.gif)
![Japanese](../../../image/japanese.gif)
![Researcher](../image/title.gif)
![Photo](../../../researcher/1ki/image/hoshino.jpg)
![Takahiro Hoshino](image/hoshino.gif)
Nagoya University Graduate School of Economics Associate Professor
![Research Site](../image/site.gif)
![Theme](../image/theme.gif)
![Abstract](../image/abstract.gif)
To make precise forecasts in policy decision making or marketing, it is necessary, but difficult to get a single-source dataset in which every variables are observed for every subjects (or units). In this research project, the purpose is to develop statistical data fusion methods for multi-source datasets in which some variables are missing for subjects, by using covariate information and imputation of missing values.
![Copyright © Japan Science and Technology ,All Right Reserved.](../../../image/copy.gif)