FRG: Collaborative Research: Statistical Inference for High-Dimensional Data: Theory, Methodology and Applications

FRG:协作研究:高维数据的统计推断:理论、方法和应用

基本信息

  • 批准号:
    0854975
  • 负责人:
  • 金额:
    $ 33万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-08-01 至 2013-07-31
  • 项目状态:
    已结题

项目摘要

The analysis of high-dimensional data sets now commonly arising in scientific investigations poses many statistical challenges not present in smaller scale studies. Extracting information with precision from such data is becoming ever more important. This FRG proposal is the PIs' unified effort to respond to the pressing scientific needs. Specifically, The goals are to develop a comprehensive theoretical framework and general methodologies for estimating a large covariance matrix and its functionals and for functional data regression where the predictors and/or the responses involve functional measurements, and to address a wide range of important applications in biomedical studies. The statistical and scientific objectives outlined in this proposal are at the intellectual center of a rapidly growing field in statistics and biostatistics. The new technical tools, inference procedures, and computing algorithms for analyzing high-dimensional data will greatly facilitate scientific investigations in a wide range of disciplines, These fields include astronomy, biology, chemistry, bioinformatics, and particularly in medicine. The proposed efficient analytical procedures hold great potential in deriving more accurate prediction rules for clinical outcomes based on new biological and genetic markers and thus may lead to a better understanding of disease processes. Research results from this proposal will be disseminated through the workshops and seminar series such that the methods would be publicly available to researchers in other disciplines. Software tools developed will be made freely and publicly available as open source code. The proposed project will also bring high-quality training to students and postdoctoral researchers.
高维数据集的分析,现在通常出现在科学调查带来了许多统计上的挑战,不存在于较小规模的研究。从这些数据中精确地提取信息变得越来越重要。这个联邦政府的建议是PI的统一努力,以应对迫切的科学需求。具体来说,我们的目标是开发一个全面的理论框架和一般方法,估计一个大的协方差矩阵和它的功能和功能数据回归的预测和/或响应涉及功能测量,并解决广泛的重要应用在生物医学研究。本提案中概述的统计和科学目标是统计和生物统计学快速发展领域的知识中心。用于分析高维数据的新技术工具、推理程序和计算算法将极大地促进广泛学科的科学研究,这些领域包括天文学、生物学、化学、生物信息学,特别是医学。所提出的有效的分析程序具有很大的潜力,在推导出更准确的预测规则的基础上,新的生物和遗传标记的临床结果,从而可能会导致更好地了解疾病的过程。这一建议的研究结果将通过讲习班和系列研讨会传播,以便其他学科的研究人员可以公开获得这些方法。所开发的软件工具将作为开放源码免费向公众提供。拟议的项目还将为学生和博士后研究人员提供高质量的培训。

项目成果

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会议论文数量(0)
专利数量(0)

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Huibin Zhou其他文献

Three-Dimensional Adaptive Modulation and Coding for DDO-OFDM Transmission System
DDO-OFDM传输系统的三维自适应调制与编码
  • DOI:
    10.1109/jphot.2017.2690691
  • 发表时间:
    2017-04
  • 期刊:
  • 影响因子:
    2.4
  • 作者:
    Xi Chen;Zhenhua Feng;Ming Tang;Borui Li;Huibin Zhou;Songnian Fu;Deming Liu
  • 通讯作者:
    Deming Liu
Near-Diffraction- and Near-Dispersion-Free OAM Pulse Having a Controllable Group Velocity by Coherently Combining Different Bessel Beams Based on Space-Time Correlations
基于时空相关性的不同贝塞尔光束相干组合获得群速度可控的近衍射和近色散OAM脉冲
  • DOI:
    10.1364/fio.2020.fm7c.7
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    K. Pang;K. Zou;Hao Song;Zhe Zhao;A. Minoofar;Runzhou Zhang;Cong Liu;Haoqian Song;Huibin Zhou;X. Su;N. Hu;M. Tur;A. Willner
  • 通讯作者:
    A. Willner
Utilizing multiplexing of structured THz beams carrying orbital-angular-momentum for high-capacity communications.
利用携带轨道角动量的结构化太赫兹光束的复用进行高容量通信。
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Huibin Zhou;X. Su;A. Minoofar;Runzhou Zhang;K. Zou;Hao Song;K. Pang;Haoqian Song;N. Hu;Zhe Zhao;A. Almaiman;S. Zach;M. Tur;A. Molisch;Hirofumi Sasaki;Doohwan Lee;A. Willner
  • 通讯作者:
    A. Willner
Free-space mid-IR communications using wavelength and mode division multiplexing
使用波长和模分复用的自由空间中红外通信
  • DOI:
    10.1016/j.optcom.2023.129518
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    2.4
  • 作者:
    A. Willner;K. Zou;K. Pang;Hao Song;Huibin Zhou;A. Minoofar;X. Su
  • 通讯作者:
    X. Su
Experimental Demonstration of Tunable Space-Time Wave Packets Carrying Time- and Longitudinal-Varying OAM
携带时变和纵变OAM的可调谐时空波包的实验演示
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    X. Su;K. Zou;Huibin Zhou;Hao Song;Yuxiang Duan;M. Karpov;T. Kippenberg;M. Tur;D. Christodoulides;A. Willner
  • 通讯作者:
    A. Willner

Huibin Zhou的其他文献

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{{ truncateString('Huibin Zhou', 18)}}的其他基金

Overparameterization, Global Convergence of the Expectation-Maximization Algorithm, and Beyond
过度参数化、期望最大化算法的全局收敛及其他
  • 批准号:
    2112918
  • 财政年份:
    2021
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
Statistical and Computational Guarantees of Three Siblings: Expectation-Maximization, Mean-Field Variational Inference, and Gibbs Sampling
三兄弟的统计和计算保证:期望最大化、平均场变分推理和吉布斯采样
  • 批准号:
    1811740
  • 财政年份:
    2018
  • 资助金额:
    $ 33万
  • 项目类别:
    Continuing Grant
Optimal Estimation of Statistical Networks
统计网络的最优估计
  • 批准号:
    1507511
  • 财政年份:
    2015
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
Empirical Process and Modern Statistical Decision Theory
经验过程与现代统计决策理论
  • 批准号:
    1534545
  • 财政年份:
    2015
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
Estimation of Functionals of High Dimensional Covariance Matrices
高维协方差矩阵泛函的估计
  • 批准号:
    1209191
  • 财政年份:
    2012
  • 资助金额:
    $ 33万
  • 项目类别:
    Continuing Grant
Innovation and Inventiveness in Statistical Methodologies
统计方法的创新和创造性
  • 批准号:
    0852498
  • 财政年份:
    2008
  • 资助金额:
    $ 33万
  • 项目类别:
    Standard Grant
CAREER: Asymptotic Statistical Decision Theory and Its Applications
职业:渐近统计决策理论及其应用
  • 批准号:
    0645676
  • 财政年份:
    2007
  • 资助金额:
    $ 33万
  • 项目类别:
    Continuing Grant

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