multivariate

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Related to Multivariate statistics: multivariate analysis

mul·ti·var·i·ate

 (mŭl′tē-vâr′ē-ĭt, -āt′, -văr′-, -tī-)
adj.
Having or involving more than one variable: multivariate statistical analysis.

multivariate

(ˌmʌltɪˈvɛərɪɪt)
adj
(Statistics) statistics (of a distribution) involving a number of distinct, though not usually independent, random variables
ThesaurusAntonymsRelated WordsSynonymsLegend:
Adj.1.multivariate - pertaining to any procedure involving two or more variables
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
variable - liable to or capable of change; "rainfall in the tropics is notoriously variable"; "variable winds"; "variable expenses"
References in periodicals archive ?
Results were analyzed by univariate and multivariate statistics.
The book covers statistical modeling and machine learning, multiple testing, parameter estimation and multivariate statistics, distance-based clustering, mixture models and hidden variables for clustering, and a wide variety of other related subjects.
These models will be tested using advanced multivariate statistics in order to detect first, the existence of effective changes in the site occupation intensities, and second the importance of the demographic variable in the MP-UP transition.
The study made use of tools in geometric morphometrics (GM) which combine the powerful and flexible tool of multivariate statistics with explicit consideration of spatial relatives of parts and therefore make it possible to investigate morphological variation with different reference to the anatomical context of the structure under study [9][10] [11].
Multivariate statistics are also discussed, but no prior knowledge is needed.
These methods were divided into: descriptive statistics, frequency study, analysis of variance, means comparison test, non-parametric tests, regression, correlation, multivariate statistics, meta-analysis (combines in a single summary measure the results of independent studies), and modeling (development and application of equations of prediction, calibration, validation; study of residuals, and others).
The package is remarkable for its choice of tools, namely experimental design (DOE) and multivariate statistics.
It offers explanations of the basic tools and exact distributional results of multivariate statistics, statistical methods for high-dimensional data, and bootstrap approximations from a methodological perspective.
7832 Multivariate Statistics and F Approximations Statistic Value Wilks' Lambda 0.
In their work, the use of multivariate statistics for process monitoring and model predictions is suggested to deal with correlations in the variables.

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