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非参数位置—尺度模型的极小极大收敛速率AI 解读

This paper studies minimax rates of convergence for nonparametric location-scale models, which include mean, quantile, expectile and momentile regression settings. Under Hellinger differentiability on the error distribution and other mild conditions, we show that the minimax rate of convergence for estimating the regression function under the squared L2 loss is determined by the metric entropy of the nonparametric function class. Different error distributions, including…

连锁不平衡评分回归及跨祖源扩展的高维统计推断AI 解读

Linkage disequilibrium score regression (LDSC) has emerged as an essential tool for genetic and genomic analyses of complex traits, utilizing high-dimensional data derived from genome-wide association studies (GWAS). LDSC computes the linkage disequilibrium (LD) scores using an external reference panel, and integrates the LD scores with only summary data from the original GWAS. In this paper, we investigate LDSC within a fixed-effect data integration framework, underscoring…

高维遗传数据预测中的分块估计与参考面板估计AI 解读

Genetic prediction holds immense promise for translating genetic discoveries into medical advances. As the high-dimensional covariance matrix (or the linkage disequilibrium (LD) pattern) of genetic variants often presents a block-diagonal structure, numerous methods account for the dependence among variants in predetermined local LD blocks. Moreover, due to privacy considerations and data protection concerns, genetic variant dependence in each LD block is typically estimated…

数据资源不平衡下的跨祖源遗传相关性估计AI 解读

The aim of this paper is to propose a novel method for estimating trans-ancestry genetic correlations in genome-wide association studies (GWAS) using genetically-predicted observations. These correlations describe how genetic architecture of complex traits varies among populations. Our new estimator corrects for biases arising from prediction errors in high-dimensional weak GWAS signals, while addressing the ethnic diversity inherent in GWAS data, such as linkage…