报告题目：A new model for data with qualitative and quantitative responses

报告所属学科：管理科学与工程

报告人：康晓宁（东北财经大学）

报告时间：2021年11月12日 09:00-10:30

报告地点：腾讯会议ID: 104 435 262

报告摘要：

In many scientific areas, data with mixed quantitative and qualitative (QQ) responses are commonly encountered with a large number of predictors. By exploring the association between QQ responses, existing approaches often consider a joint model of QQ responses given the predictor variables. However, the dependency among predictive variables also provides useful information for fitting QQ responses. Hence in this work, we propose a novel approach to jointly model the QQ responses by incorporating the dependency information of predictors. The proposed method is computationally efficient and provides accurate parameter estimation under a penalized likelihood framework. Moreover, the asymptotically theoretical results of the proposed method in terms of classification rate and prediction accuracy are established under some regularity conditions. The performance of the proposed method is examined through simulations and real case studies in genetics.

报告人简介：

康晓宁，东北财经大学副教授，硕士生导师。本科、硕士毕业于大连理工大学数学系，博士毕业于美国弗吉尼亚理工大学统计系。主要研究领域包括高维矩阵的估计及应用、混合数据建模、半参数模型的统计推断、贝叶斯统计等。曾先后主持和参与国家自然科学基金、教育部人文社科基金、辽宁省教育厅基金等项目。其研究成果已发表在IISE Transactions, Journal of Quality Technology, International Statistical Review, Computational Statistics & Data Analysis等国际期刊上。