主题: Challenges in Age-Period-Cohort Models and Applications to Economics, Marketing and Health Research
主讲人：Wenjiang Fu,University of Huston
Wenjiang Fu教授是休斯顿大学数学系统计学教授。他的主要研究领域为针对复杂和高维数据的统计建模与计算。同时，他的研究关注数学与统计学模型在经济学、市场营销以及公共卫生领域的应用。Wenjiang Fu教授的研究在公共卫生领域有重大影响，他本人主持和参与了多项NIH/CDC大型课题。Wenjiang Fu教授的著作丰富，其多项研究先后发表在JASA, Annals of Statistics, Bioinformatics等国际顶级学术杂志上。
In economics, marketing research and business management, it is important to estimate the temporal trend of sales of products or the market share of a business during a period of time. In public health likewise, it is crucial to estimate the temporal trend of chronic disease (cancer, cardiovascular diseases, etc.) mortality rates. Often the sales of products vary with the age of consumers (e.g. sales of cosmetic products or life insurance policies), and the mortality rate varies with the age of patients (e.g. mortality rate of breast cancer), thus are reported by age group. More importantly, they also vary largely with the cohort (or generation) effect, which shows large difference between the older generations and younger generations. This presents a major challenge in statistical modeling - the identifiability problem in regression models with linearly dependent covariates, which has perplexed the statistical community for decades. I will present this complicated problem using simple graphical method, and present the most recent advances in addressing this identifiability problem. I will also demonstrate some novel methods with economics, public health and insurance policy purchase data.