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面向肥胖遗传变异的超高维数据知识整合分位数回归方法AI 解读

Obesity is widely recognized as a serious and pervasive health concern. We study obesity through body mass index (BMI), which is known to be highly heritable, and identify important genetic risk factors for BMI from hundreds of thousands of single nucleotide polymorphisms (SNPs) in the Framingham Study data. Several challenges arise when using traditional genome-wide association studies (GWAS): (1) They suffer from a low power due to a combination of a limited number of…

面板数据模型中追寻同质分组的非参数分位数回归AI 解读

Many panel data have the latent subgroup effect on individuals, and it is important to correctly identify these groups since the efficiency of resulting estimators can be improved significantly by pooling the information of individuals within each group. However, the currently assumed parametric and semiparametric relationship between the response and predictors may be misspecified, which leads to a wrong grouping result, and the nonparametric approach hence can be…