Local disclosure control techniques of statistical microdata sets

本年度，在统计微观数据的披露控制技术方面取得了重要成果。竹村在国际统计学会（International Statistical Institute）的会议上，以“Evaluation of per-record identification risk by additive modeling of interaction for contingency table cell probabilities”为题发表了特邀演讲。这篇论文将被收入国际测量统计学家协会出版的一份单独的论文集。论文“Minimum unsafe and maximum safe sets of variables for disclosure risk assessment of individual records in a microdata set”将发表在日本统计学会会刊星野信明的论文“On application of皮特曼's sampling formula to microdata disclosure risk assessment”发表在官方统计杂志上。作为一项新的研究成果，两篇讨论论文“关于条件逆高斯-泊松分布的随机聚类”和“关于条件逆高斯-泊松分布导出的限制随机划分结构”作为讨论论文在卡内基梅隆大学发表。

We obtained several important results on the disclosure control techniques of statistical microdata sets in this year.Takemura gave an invited talk on the paper "Evaluation of per-record identification risk by additive modeling of interaction for contingency table cell probabilities" at the meeting of International Statistical Institute. This paper will be included in a separate proceedings published by International Association of Survey Statisticians. A paper "Minimum unsafe and maximum safe sets of variables for disclosure risk assessment of individual records in a microdata set" will be published in Journal of Japan Statistical Society The paper "On application of Pitman's sampling formula to microdata disclosure risk assessment" by Nobuaki Hoshino was published in Journal of Official Statistics. As a new research results, two discussion papers "On the random clustering with the conditional inverse Gaussian-Poisson distribution" and "On limiting random partition structure derived from the conditional inverse Gaussian-Poisson distribution" are published as discussion paper in Carnegie Mellon university.