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The nonlinear part of these models can be a more general multivariate polynomial function.
These methods make use of the raw expression data, and some of them are based on logistic regression models while others utilize Hotelling's t-tests or the more general multivariate analysis of variance models.
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For a more general model a multivariate (c-variate) distribution of measurement error can be used (See Definition of functions assuming multivariate measurement error probability density functions in Appendix S1).
It is not only a correction procedure, but a more general approach for multivariate data analysis.
Here we prove the more general case of multivariate embeddings (embeddings using multiple time series and lags thereof), and show how time series information can be leveraged if multiple time series and their lags are used to construct embeddings of <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0018295.e010.PNG" class= inline-graphic"/>.
Multivariate calculus is a more general mathematical branch which paly a more important role in mathematical and applied fields.
Meanwhile, the multivariate ZACS distribution, as a more general form, can be used in a much wider range.
So we consider about using PLS method, a more general method, which can deal with all types of multivariate series.
CBA utilises the data from regions or VOIs able to feed multivariate analysis enabling the investigation of more general statistical effects.
Focusing therefore on a more general model, we compare alternative structures with respect to a multivariate optimization criterion.
Extensions to joint modelling of multivariate extremes, incorporating extremal spatial dependence (using max-stable processes) or more general extremal dependence (using the conditional extremes approach) are outlined.
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