Studies on disclosure control of microdata and statistical analysis of disclosed data

本课题组多年来在微观数据的披露控制及其应用领域取得了许多有意义的成果，在本课题组前期编辑了《统计数学研究所学报》第51卷第2期（2003年12月出版）的关于披露控制技术理论研究的专题卷。这个特别的卷包含超过200页的评论和原始结果，我们的小组和许多人开始意识到这一领域的重要性和前景。在重要的问题估计人口uniques在微观数据集，星野获得了许多显着的原始结果扩展的皮特曼模型和混合泊松模型的一类新的分布的随机分区。此外，Sai的非参数极大似然估计经过多次改进后，对于实际的官方微观数据集变得可行和实用。此外，正如应我们邀请访问日本的Fienberg教授所指出的，我们意识到“计算代数统计”这一新领域在披露控制问题上的重要应用。基于这一思想，武村建立了一个统一的战略，披露风险评估和披露控制使用分解模型。

Throughout the years of this research our group obtained many significant results in the field of disclosure control of microdata and its applications.Early in this research period our group edited a special volume (No.2 of Volume 51, December of 2003) of Proceedings of the Institute of Statistical Mathematics published by Institute of Statistical Mathematics on the topic of theoretical research of disclosure control techniques. This special volume contains more than 200 pages of reviews and original results of our group and many people became aware of the importance and promise of this field.On the important problem of estimation of population uniques in a microdata set, Hoshino obtained many remarkable original results extending the Pitman model and mixed Poisson model to a new class of distributions of random partitions. Furthermore non-parametric maximum likelihood estimation by Sai became feasible and practical for actual official microdata sets after many improvements.Furthermore as pointed out by Prof.Fienberg, who visited Japan by our invitation, we became aware of the important application of the new field of "computational algebraic statistics" to disclosure control problems. Based on this idea, Takemura established a unified strategy of disclosure risk assessment and disclosure control using decomposable models.