1)  multivariate statistical control chart

1.
According to the operation experiences in real processes, some rules are proposed by which operator can judge whether the process is under control or not when monitoring the multivariate statistical control charts.

2)  multivariate control chart

1.
These are: the M-chart for detecting linear trends; the PP-CUSUM charts for detecting small mean shift; and multivariate control charts for short-run processes.

3)  multi-dimensional statistical chart

4)  Multivariate statistical process control

1.
Squared prediction error (SPE) statistic is frequently used in multivariate statistical process control and its law of variation needs further investigating.

5)  multivariable statistical process control

1.
The work in this thesis is based on three technologies of Multivariable Statistical Process Control(MSPC), the Principal Component Analysis(PCA), the Partial Least Squares(PLS) and the Kernel Density Estimate(KDE).

6)  multivariate statistical techniques

1.
Based on principle component model, detection and diagnosis analysis is carried out on a typical Heavy Oil Fractionator with multivariate statistical techniques such as Q residuals plot, Retelling T2 plot, principle .

 多元统计分析multivariate statistical analysis    研究客观事物中多个变量（或多个因素）之间相互依赖的统计规律性。它的重要基础之一是多元正态分析。又称多元分析 。 如果每个个体有多个观测数据，或者从数学上说， 如果个体的观测数据能表为 P维欧几里得空间的点，那么这样的数据叫做多元数据，而分析多元数据的统计方法就叫做多元统计分析 。 它是数理统计学中的一个重要的分支学科。20世纪30年代，R.A.费希尔，H.霍特林，许宝以及S.N.罗伊等人作出了一系列奠基性的工作，使多元统计分析在理论上得到迅速发展。50年代中期，随着电子计算机的发展和普及 ，多元统计分析在地质 、气象、生物、医学、图像处理、经济分析等许多领域得到了广泛的应用 ，同时也促进了理论的发展。各种统计软件包如SAS，SPSS等，使实际工作者利用多元统计分析方法解决实际问题更简单方便。重要的多元统计分析方法有：多重回归分析（简称回归分析）、判别分析、聚类分析、主成分分析、对应分析、因子分析、典型相关分析、多元方差分析等。