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To model nonlinear hybrid systems, Nandola and Bhartiya [3] proposed a multiple linear model approach wherein multiple linear models are used to describe the dynamic behavior in each mode of the hybrid system.
A multiple linear model is considered, where the magnitudes calculated from the sum of all axes acceleration vibration and average speed are set as explanatory variables.
Independent variables has been used in logit model are about same as presented in multiple linear model in this paper with the exception of family and community employment and income.
Although PLAND explained 88% of the variation in IIC in a simple linear model, a significant partial quadratic term (F 1110 = 810, P <0.0001) in a multiple linear model indicated that IIC changed in a nonlinear fashion with changes in PLAND.
A multiple linear model was used to test for difference between genotype groups assuming an additive model in quantitative trait studies.
The General Linear Model (GML) and Multiple Linear Model (MLM) implemented in TASSEL software [ 63, 80] were applied.
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Empirical models were formulated based on multiple linear models.
The piecewise linear regression allows multiple linear models to be fitted, and where the lines meet can be used to identify breakpoints where the slope of the linear function changes.
Mini-max optimisation algorithms are used for the design of robust controllers based on the multiple linear models.
Thus, 88 categories of the ICF Core Set for neurological conditions were retained for the multiple linear models.
As such, a statistical analysis employing a multiple linear modelling procedure is considered beneficial.
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