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Indeed, in this paper, we restrict the analysis to the simple case of regression of one explanatory variable (X) and one response variable (Y ), however the models can easily be extended to the multiple regression case, and also to the multivariate response case.
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Adaptive estimation of the rank of the coefficient matrix in high dimensional multivariate response regression models.
A new method of processing multivariate response data to extract chemical information has been developed.
The optimization of the extraction conditions was carried out using multivariate response surface methodology.
Hard modeling approaches of fitting multivariate response data are based on mathematical relationships, which describe the measurements quantitatively [14]‐[16].
In the current experiments, the dependent AEP (or HGB power) measurement was treated as a multivariate response and assumed to be sampled from a multivariate distribution [34].
Many multivariate regression techniques are designed for univariate response cases.
Methods for multivariate responses.
Van den Brink, P. J. & Ter Braak, C. J. F. Principal response curves: analysis of time-dependent multivariate responses of a biological community to stress.
Designs for multivariate responses can likewise be found, requiring only the appropriate information matrix.
Some new results in the theory of optimum experimental design for multivariate responses are presented.
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