Sentence examples for multivariate responses and from inspiring English sources

Our results illustrate that the multi-objective optimization provides a balanced solution for multivariate responses and gives better representation of streamflow and LAI dynamics.

Finally, the orthogonal LS PLS method is extended to multivariate responses and used to identify the source of the observed block effect and to build models that can be used for statistical process control at several points in the process.

The UMA handles the measurements in the subject as a vector of multivariate responses and treats time points as levels of a qualitative factor with no order.

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].

These models also allow for a multivariate response, and incorporate incomplete data.

In all regressions, the 8 PCs associated with NEFD defined the multivariate response and the independent variables considered were: the bio-anthropometric, height and population.

For many chemicals, we observed the effects of genotype both for EC10 and across the multivariate response, and the two approaches provided similar evidence (see Supplemental Material, Figure S5).

Sites 12 and 15 represent different research centers within one company, as do sites 3 and 5. HL was computed using the first ten principal components as a multivariate response, and then standardized to be between 0 and 1 by dividing by HL statistic for the maximal model consisting of all distinct factor combinations.

The application of this approach is limited by the fact that estimation of mixed models is computationally infeasible for multivariate responses of dimension four and larger [ 19].

MAGWAS is a computationally efficient, user‐friendly, open source software tool that works on most platforms and performs GWASs for individuals having multivariate responses using standard file formats.

Furthermore, the GEMANOVA model has additional advantages such as the possibility of readily including multivariate responses (e.g., an entire spectral data set), model uniqueness, and curve resolution abilities.