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Furthermore, sensitivity analysis of solutions presented the robustness of solution of these methods under parametric uncertainty.
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Because of the parametric resampling of the link weights, this method formally falls under parametric bootstrapping.
Generally speaking, when either the assumption of normality or homoscedasticity or both are violated, highly inflated type I errors and false positives can arise, suggesting a non-robustness of parametric methods under these scenarios [ 9].
The statistical parameters (mean, standard deviation) of the samples from the four different clustering methods were calculated because they described the distribution of each sample under parametric statistics.
In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load).
In ZKV and CCV methods, different parametric values are optimized to suppress the impulsive noise under fading conditions in the presence of perfect CSI.
Subsequently, the method is applied to study the dynamical instability and parametric resonance of Duffing oscillator with hardening spring under parametric excitation of bounded noise.
e Stationary watermark under parametric attack.
f Non-stationary watermark under parametric attack.
Some methods include parametric and non-parametric background density estimates and spatial correlation approaches [10].
Under parametric model assumptions the expressions can be further developed.
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