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1)  multivariate linear statistical analysis
多元线性统计
1.
The spatial and temporal distribution of PM10 concentration statistic of seven monitoring sites in one year was contrastively analyzed,and the multivariate linear statistical analysis of the factors affecting PM10 concentration in spring and winter was also carried out.
对哈尔滨市七个监测点全年PM10浓度数据做了时间、空间上的对比分析,并对春、冬季影响PM10浓度变化的因素进行了多元线性统计分析。
2)  Multi-fact linearity Statistic
多元线性相关统计
3)  multivariate linear Minimax estimation
多元线性Minimax估计
4)  multivariate statistics
多元统计
1.
Source identification of PAHs in surface sediments from Bohai Sea by multivariate statistics;
多元统计在渤海表层沉积物中PAHs源解析上的应用
2.
Application of multivariate statistics in study on combinative characteristics of indicator elements:an example from Huangbuling gold deposit in Shandong,China;
多元统计分析在矿床指示元素组合特征研究中的应用——以山东黄埠岭金矿为例
3.
The PCA(principal component analysis) of multivariate statistics is applied to the performance evaluation system with a telecom enterprise taken as multi-objective example to analyze.
将多元统计中的主成分分析法运用于电信企业绩效评价体系中,并针对实例进行了分析和评价。
5)  multivariate statistical analysis
多元统计
1.
15 indexes were chosen,using multivariate statistical analysis techniques(Principle Component Analysis and Canonical Correspondence Analysis),the complex relationships between the soil properties,plant biodiversity and landform factors were examined.
利用多元统计方法,对选取的指标进行了主成分分析和典范相关分析。
6)  multivariate statistical
多元统计
1.
Welding quality analysis of GMAW process based on multivariate statistical analysis of electric signal;
基于电信号多元统计的GMAW焊接质量分析方法
2.
The multivariate statistical method is introduced in the paper to analyze conventional statistical operators of partial discharge (PD).
采用多元统计分析方法对传统的局部放电统计特征算子进行了因子分析,从24个统计算子中提取出8个公共因子作为局部放电新特征因子,从而实现数据压缩的目的。
3.
The paper preliminary explored the growth modeling method of the plant tissue culture seedling based on multivariate statistical information fusion technology for the physiological growth research, then created a model in MINITAB for a better prediction of the plant growth analysis and verified its feasibility and accuracy of the growth modeling for the foundation of the next phase in-depth study.
首先基于CO_2传感器,温度传感器及相对湿度传感器,采用卡尔曼滤波特征级方法对组培苗生长信息进行多传感器信息融合及计算机仿真,其次,借助Minitab15软件融合信息进行多元统计分析,应用Logistic回归方程对组培苗进行生长建模。
补充资料:多元
1.多种多样。
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