Boosting AI-Generated Biomedical Images with Confidence through Advanced Statistical Inference [0.03%]
基于高级统计推理提升AI生成的生物医学图像的信心度
Zhiling Gu,Shan Yu,Guannan Wang et al.
Zhiling Gu et al.
Generative artificial intelligence (AI) has transformed the biomedical imaging field through image synthesis, addressing challenges of data availability, privacy, and diversity in biomedical research. This paper proposes a novel nonparametr...
Xu Guo,Runze Li,Zhe Zhang et al.
Xu Guo et al.
This paper aims to develop an effective model-free inference procedure for high-dimensional data. We first reformulate the hypothesis testing problem via sufficient dimension reduction framework. With the aid of new reformulation, we propos...
Statistical Inference of Cell-type Proportions Estimated from Bulk Expression Data [0.03%]
基于bulk表达数据的细胞类型比例的统计推断
Biao Cai,Emma Jingfei Zhang,Hongyu Li et al.
Biao Cai et al.
There is a growing interest in cell-type-specific analysis from bulk samples with a mixture of different cell types. A critical first step in such analyses is the accurate estimation of cell-type proportions in a bulk sample. Although many ...
Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces [0.03%]
度量空间中通过度量分布函数进行非参数统计推断
Xueqin Wang,Jin Zhu,Wenliang Pan et al.
Xueqin Wang et al.
The distribution function is essential in statistical inference and connected with samples to form a directed closed loop by the correspondence theorem in measure theory and the Glivenko-Cantelli and Donsker properties. This connection crea...
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies [0.03%]
极大极小效应的统计推断：跨多个研究识别稳定的关联
Zijian Guo
Zijian Guo
Integrative analysis of data from multiple sources is critical to making generalizable discoveries. Associations consistently observed across multiple source populations are more likely to be generalized to target populations with possible ...
Statistical Inferences for Complex Dependence of Multimodal Imaging Data [0.03%]
多模态影像数据复杂相关性的统计推断方法研究
Jinyuan Chang,Jing He,Jian Kang et al.
Jinyuan Chang et al.
Statistical analysis of multimodal imaging data is a challenging task, since the data involves high-dimensionality, strong spatial correlations and complex data structures. In this paper, we propose rigorous statistical testing procedures f...
Statistical Inference for High-Dimensional Generalized Linear Models with Binary Outcomes [0.03%]
高维广义线性模型二值响应变量的统计推断方法研究
T Tony Cai,Zijian Guo,Rong Ma
T Tony Cai
This paper develops a unified statistical inference framework for high-dimensional binary generalized linear models (GLMs) with general link functions. Both unknown and known design distribution settings are considered. A two-step weighted ...
Zhe Fei,Qi Zheng,Hyokyoung G Hong et al.
Zhe Fei et al.
With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged a...
Selection-Corrected Statistical Inference for Region Detection With High-Throughput Assays [0.03%]
高通量测定中用于区域检测的选择修正统计推断
Yuval Benjamini,Jonathan Taylor,Rafael A Irizarry
Yuval Benjamini
Scientists use high-dimensional measurement assays to detect and prioritize regions of strong signal in spatially organized domain. Examples include finding methylation enriched genomic regions using microarrays, and active cortical areas u...
Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation [0.03%]
高维模型的统计推断及递归在线评分估计方法
Chengchun Shi,Rui Song,Wenbin Lu et al.
Chengchun Shi et al.
In this paper, we develop a new estimation and valid inference method for single or low-dimensional regression coefficients in high-dimensional generalized linear models. The number of the predictors is allowed to grow exponentially fast wi...