Statistical Data Fusion for Advanced Use of Multi-source Datasets
Finished by March 31, 2012
Nagoya University Graduate School of Economics Associate Professor
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.