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Population-level Balance in Signed Networks 签名网络中人口层面的平衡
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2356894
Weijing Tang, Ji Zhu
Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for signed networks have been largely...
统计网络模型有助于了解复杂网络的基本形成机制和特征。然而,签名网络的统计模型在很大程度上...
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引用次数: 0
Doubly Robust Augmented Model Accuracy Transfer Inference with High Dimensional Features 具有高维特征的双稳健增强模型精度转移推理
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2356291
Doudou Zhou, Molei Liu, Mengyan Li, Tianxi Cai
Transfer learning is crucial for training models that generalize to unlabeled target populations using labeled source data, especially in real-world studies where label scarcity and covariate shift...
迁移学习对于利用带标记的源数据训练可泛化到无标记目标人群的模型至关重要,尤其是在现实世界的研究中,因为在现实世界中,标记稀缺且共变因素会发生变化...
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引用次数: 0
Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle 利用 Muscle 对单细胞三维基因组和表观遗传数据进行联合张量建模
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-21 DOI: 10.1080/01621459.2024.2358557
Kwangmoon Park, Sündüz Keleş
Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional...
同时捕捉基因组位点长程相互作用及其 DNA 甲基化水平的新兴单细胞技术正在推进我们对三维基因组学的理解。
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引用次数: 0
Neural networks for geospatial data 用于地理空间数据的神经网络
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-20 DOI: 10.1080/01621459.2024.2356293
Wentao Zhan, Abhirup Datta
Abstract–Analysis of geospatial data has traditionally been model-based, with a mean model, customarily specified as a linear regression on the covariates, and a Gaussian process covariance model, ...
摘要--地理空间数据分析传统上以模型为基础,平均值模型(通常指定为对协变因素的线性回归)和高斯过程协方差模型(通常指定为对协变因素的线性回归)都是基于模型的。
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引用次数: 0
Rational Kriging 理性克里金法
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-20 DOI: 10.1080/01621459.2024.2356296
V. Roshan Joseph
This article proposes a new kriging that has a rational form. It is shown that the generalized least squares estimator of the mean from rational kriging is much more well behaved than that of ordin...
本文提出了一种具有合理形式的新克里金法。结果表明,合理克里金法的广义最小二乘法均值估计值比普通克里金法的均值估计值表现得更好。
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引用次数: 0
Distribution-Free Prediction Intervals Under Covariate Shift, With an Application to Causal Inference 变量偏移下的无分布预测区间,在因果推理中的应用
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-20 DOI: 10.1080/01621459.2024.2356886
Jing Qin, Yukun Liu, Moming Li, Chiung-Yu Huang
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引用次数: 0
Tests for large-dimensional shape matrices via Tyler’s M estimators 通过泰勒 M 估计数测试大维度形状矩阵
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-05-03 DOI: 10.1080/01621459.2024.2350573
Runze Li, Weiming Li, Qinwen Wang
Tyler’s M estimator, as a robust alternative to the sample covariance matrix, has been widely applied in robust statistics. However, classical theory on Tyler’s M estimator is mainly developed in t...
泰勒 M 估计器作为样本协方差矩阵的稳健替代方法,已被广泛应用于稳健统计中。然而,Tyler's M 估计器的经典理论主要是在统计学中发展起来的。
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引用次数: 0
Controlled Discovery and Localization of Signals via Bayesian Linear Programming 通过贝叶斯线性规划控制信号的发现和定位
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-04-26 DOI: 10.1080/01621459.2024.2347667
Asher Spector, Lucas Janson
Scientists often must simultaneously localize and discover signals. For instance, in genetic fine-mapping, high correlations between nearby genetic variants make it hard to identify the exact locat...
科学家往往必须同时定位和发现信号。例如,在基因精细图谱中,附近基因变异之间的高度相关性使得很难确定信号的确切位置。
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引用次数: 0
Testing the number of common factors by bootstrapped sample covariance matrix in high-dimensional factor models 在高维因子模型中通过引导样本协方差矩阵检验公共因子的数量
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-04-22 DOI: 10.1080/01621459.2024.2346364
Long Yu, Peng Zhao, Wang Zhou
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引用次数: 0
Estimating trans-ancestry genetic correlation with unbalanced data resources 利用不平衡数据资源估算跨宗族遗传相关性
IF 3.7 1区 数学 Q1 Mathematics Pub Date : 2024-04-19 DOI: 10.1080/01621459.2024.2344703
Bingxin Zhao, Xiaochen Yang, Hongtu Zhu
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 corre...
本文旨在提出一种新方法,利用基因预测观察结果估算全基因组关联研究(GWAS)中的跨祖先遗传相关性。这些相关...
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引用次数: 0
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Journal of the American Statistical Association
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