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In the presented study, orthogonal projection to latent structures (OPLS) is introduced as a data preprocessing method that handles nonlinear data prior to modelling with two well established nonlinear multivariate models; namely support vector regression (SVR) and artificial neural networks (ANN).
I test linearity in the dose response by modelling with two nested non-linear models, each of which contains the linear model.
We demonstrate the impact of temporal aspects in accessibility modelling with two examples: by investigating food accessibility and its spatial equity.
A non-trivial behaviour of transient current responses revealed in the HD modelling with two prominent features (space charge injection and the velocity overshoot, as was discussed in the previous section) and complete absence of these effects in the DD modelling clearly indicate that the results from the DD and HD models of a Gunn diode oscillator may be profoundly different.
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The time series of the calculated recording rate was modeled with two functions.
The uncertainty in laser ranging measurements can be modeled with two main components, angular and radial.
With three knots, time is modeled with two parameters.
For AT or GC skew, the signals were modelled with two binomial distributions in each strand.
Brazilwood, cochineal and lac dye samples were modelled with four components, while kermes demanded five components.
The dependent output response has been modeled with three independent input parameters using ANOVA.
The T-shaped wall and wall-column were modeled with five and eleven macro-elements, respectively.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com