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Considering the uncertainties in the model parameters, an approximate dynamic model with uncertain parameters is formulated by classifying the uncertainties into different types, including constant parametric, variable parametric and nonparametric uncertainties.
Manohar and Divakar [ 21] employed a five variable parametric study for ANN analysis.
Finally, we estimated multiple variable parametric hazard models with continuous time frailty to account for unobserved heterogeneity in health status among subjects [ 25, 26].
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We performed a 4-variable parametric analysis of the AD-SOFC system in order to determine the optimal design operation conditions, depending on the objective function of interest.
Geometry and algebra of vectors, systems of linear equations, matrices and linear transformations, diagonalization and eigenvectors, vector valued functions and functions of several variables, parametric curves, partial derivatives and gradients, the derivative as a matrix, chain rule in several variables, constrained and unconstrained optimization.
For continuous variables, parametric or non-parametric analysis of variance will be used.
To compare between-group differences in all continuous or categorical variables, parametric or nonparametric methods were appropriately used to test statistical significance.
Depending on the characteristics of the variables, parametric and non-parametric statistics will be used, and both variable-based and person-based statistical analysis approaches [ 51] will be considered.
Continuous variables with parametric distribution were described as mean and SD, and non-parametric continuous variables and ordinal variables were described as median and first and third quartiles.
Adjustment of these variables yields parametric studies concerning the thermal stress response.
Logarithmic or square root transformations were applied as needed to ensure normal distribution of the variables, and parametric tests were applied thereafter.
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