Non-negative matrix factorization (NMF) has been proposed for multivariate data analysis, with non-negativity constraints.
非 负数据处理的一种多元统计分析方法。
By using multivariate linear regression analysis, the mathematical model to classify and evaluate reservoir with well logging data was established.
通过多元线性回归分析，建立了用多种测井信息划分、评价储层的数学模型。
Methods Univariate analysis and multivariate regression were performed on data of 117 patients with lupus nephritis, with the physicians global assessment of disease activity as the external criteria.
方法以临床医师的判断作为疾病活动程度的外部标准，对117例狼疮性肾炎患者的资料进行单因素相关分析和多元回归分析。
This paper deals with the multivariate vector analysis of quality data by geometric transformation, rotating coordinates and computation of the principal component of initial variables.
本文讨论多元质量数据的矢量分析方法，几何变换，坐标旋转和初始变量的主分量计算不同变量的主分量值。
The data were treated with univariate and multivariate analysis of variance, multiple linear regression analysis and t test.
数据处理方法包括单因素多变量方差分析、多因素线性回归分析和t检验。
Nonloss storage experiments were performed to a cryogenic vessel filled with liquid nitrogen, and a multivariate linearity regression analysis and check to the experimental data was also done.
对一低温容器利用液氮为介质进行了多次无损贮存实验，利用多元线性回归方法对实验数据进行分析和检验。
By far, the most important reason for performing a principal components analysis (PCA) is to use it as a tool for screening multivariate data.
到目前为止，最重要的原因为执行一个主成分分析(PCA)是使用它当作一个工具，用于筛选的多元数据。
The principal component analysis in multivariate statistic analysis is a method of compressing the dimension of vector data by extracting principal typical components from sample data set.
多元统计分析的主成份分析方法是对多维矢量数据提取主要特征分量，以此达到压缩矢量维数的目的。
You can carry out very comprehensive analysis of univariate and multivariate data based on linear, general linear, and mixed linear models.
你可以基于线性、广义线性、以及混合线性模型进行单变量和多变量数据的全面分析。
Multivariate analysis of the component data indicate that population Wenchuan is the most distinct.
精油组分的多变量分析得到汶川县的人工林与其它居群的相似性最小。
Firstly, we develop some new methods on the basis of graphical models, which has been widely used in data mining and multivariate analysis.
作为进行多变量数据分析的重要手段，“图模型”近年来得到了人们的广泛关注，并被应用于许多重要领域。
Principal Component Analysis (PCA) is a main multivariate statistical method for getting principal information from observational data.
主成分分析法是从观测数据中获取主要信息的一种多变量统计方法。
This paper proposes to use artificial neural network on multivariate analysis of geological data.
本文提出了利用人工神经网络进行地质数据多变量分析的方法。
Based on analysis of the data characters of batch processes, this paper presents a review of multivariate statistical performance monitoring and control of batch process.
从间歇过程独特的数据特性出发，对现有的建模和统计监控方法进行了综述，并对这一领域中依然存在的问题以及研究前景给出了中肯的评述。
Based on analysis of the data characters of batch processes, this paper presents a review of multivariate statistical performance monitoring and control of batch process.
从间歇过程独特的数据特性出发，对现有的建模和统计监控方法进行了综述，并对这一领域中依然存在的问题以及研究前景给出了中肯的评述。
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