搜索结果: 1-15 共查到“Fisher”相关记录169条 . 查询时间(0.125 秒)
关于两样本Behrens-Fisher问题，该研究在高维检验问题中取得新的进展。在此问题中，Chen & Qin (2010)所提出的检验统计量具有广泛的影响力。然而，在本项工作之前，如何在一般的条件下控制住此统计量的检验水平是一个悬而未决的问题。本文作者针对Chen & Qin (2010)的检验统计量，给出了统计量在不同的条件下所有可能的分布，提出了一种新的近似随机化检验方法，并给出其理论性质...
2021年7月28日上午，“统计大讲堂”系列讲座第165讲举行。本次讲座采取在线会议的方式，邀请新加坡国立大学概率统计系终身教授张金廷作题为“基于两样本高维数据Behrens-Fisher的Chen-Qin检验进一步研究”的报告。讲座由中国人民大学统计学院许王莉教授主持。
鲁东大学数学与统计科学学院多元统计分析课件 Fisher判别分析。
CHANGES IN VELOCITY OF FISHER GLACIER, EAST ANTARCTICA USING PIXEL TRACKING METHOD
Glacier velocity image matching Antarctica COSI-corr
2019/2/28
Glacier movement is a crucial factor for assessing cryospheric climate change. Traditional methods of field surveys for studying glacier movement and velocity are often not possible owing to inaccessi...
2017年8月31日下午，英国剑桥大学化学工程和生物技术系 Adrian Fisher教授一行4人到我院进行交流访问，我院院长李学林出席交流座谈会，院科研处、国际合作处、成果转化处、质标所、加工所、茶叶所等单位相关负责人及科技人员参加座谈。
融合Fisher线性判别分析的多维特征融合情景感知推荐方法
多特征融合 Fisher线性判别分析 属性偏好 时间衰减 情景感知推荐
2017/8/22
针对采用单维特征建立用户的偏好模型所导致的推荐结果无法有效覆盖用户潜在偏好特征而影响推荐质量的问题,提出了一种基于Fisher线性判别分析的多维特征融合情景感知推荐方法。该方法建立了包含时间衰减度、属性偏好、偏好可影响程度等多维特征的偏好样本空间;采用特征融合、投影变换等方法,在最佳鉴别矢量空间基于Fisher判别准则融合用户的多维特征;采用拉格朗日乘子法求解最优投影方向,建立起多维特征优化的偏好...
基于Fisher信息对称的信息完全测量研究进展
量子测量 Fisher信息对称 量子态
2021/9/1
量子测量，作为提取信息的基本手段，是量子信息论中一个基本而重要的概念。量子态层析是指通过对多份同一未知量子态进行量子测量，再利用测量获取的信息对量子态进行估计，以确定真实量子态的过程。如何选择量子测量以有效地获取量子态的信息是量子态层析中的一个核心问题。理想的量子测量方案中涉及的量子测量算子要尽可能少，并且在实验中要易于实现。
视频：河南师范大学数学与信息科学学院高等数理统计教学录像第七讲 Fisher信息与充分统计量
视频 河南师范大学数学与信息科学学院 高等数理统计 教学录像 第七讲 Fisher信息与充分统计量
2016/12/12
视频：河南师范大学数学与信息科学学院高等数理统计教学录像第七讲 Fisher信息与充分统计量。
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND,CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS
Polarimetric Synthetic Aperture Radar (PolSAR) Unsupervised Wishart Classification Fisher Linear Discrimination Feature Weighting
2016/11/23
Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classificatio...
The structure of idealization in biological theories:the case of the Wright-Fisher model
idealization theory biology possible worlds
2016/5/30
In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of c...
Professor Steven A. Fisher，Department of Microbiology & Immunology at University of Maryland（图）
Professor Steven A. Fisher Department of Microbiology & Immunology at University of Maryland
2015/12/31
Professor Steven A. Fisher，Department of Microbiology & Immunology at University of Maryland,Dr. Fisher’s research interests revolve around the regulation of gene expression in relation to (a) vascula...
NEW MULTICATEGORY BOOSTING ALGORITHMS BASED ON MULTICATEGORY FISHER-CONSISTENT LOSSES
MULTICATEGORY BOOSTING ALGORITHMS MULTICATEGORY FISHER-CONSISTENT LOSSES
2015/8/21
Fisher-consistent loss functions play a fundamental role in the construction of successful binary margin-based classifiers. In this paper we establish the Fisher-consistency condition for multicategor...
Professor Paul Graham Fisher,Department of Neurology&Neurological Sciences at Stanford University（图）
Department of Neurology&Neurological Sciences at Stanford University Professor Neurology
2015/8/20
Paul Graham Fisher,Professor,Department of Neurology&Neurological Sciences at Stanford University.He is Clinical Focus:Cancer > Neuro Oncology,Neurology-Child Neurology,Neuro-Oncology,Neurology.Clinic...
Professor Robert Fisher,Department of Neurology&Neurological Sciences at Stanford University（图）
Department of Neurology&Neurological Sciences at Stanford University Professor Neurology
2015/8/20
Robert Fisher is Maslah Saul MD Professor and Director of the Stanford Epilepsy Center. He had research awards from the Klingenstein Foundation, EF, CURE and NIH. He published 160 peer-reviewed articl...
Robust Fisher discriminant analysis
Fisher linear sensitive data convex model a numerical example
2015/8/10
Fisher linear discriminant analysis (LDA) can be sensitive to the problem data. Robust Fisher LDA can systematically alleviate the sensitivity problem by explicitly incorporating a model of data uncer...