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Authors of [ 54] suggested that "..sigmoid function can be considered an excellent decision support tool within any scope" and we have been able to fine tune this function by adjusting the λ value as per our data set.
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The theoretical resonance responses, with the λ value adjusted to data, for the resonance frequency of 9 Hz for are also shown for |Z11| and |Z21|.
According to the relationship between mean RMSD and λ, the λ value was set to five.
The superscripts following the λ value indicate p-value of likelihood ratio tests against models with λ = 0 (first position) and λ = 1 (second position).
The λ value from our modeling corresponding to estimated parameters from the 2008 South Korean AI epidemic was λ = 0.465.
The λ values were normally distributed.
To detect these boundary points, one has to precisely adjust the value of λ c to get different tangent points.
The amplitude factor, A, was calculated as a ratio of the standard deviation in the simulated CO2 time series (adjusted by the appropriate λ values) to the standard deviation in the observed CO2 time series (equation (4)) and therefore provides information about the magnitude of variability explained by each flux model.
In our study we tested this value by permutations, with the same number of random genes sampled from the genome and the λ-value calculated (random λ).
The blending surface has a simple exclusive G1 continuity expression; its shape can be adjusted by changing λ values.
The multi-kernel function can adapt to different input samples by adjusting the tune parameter λ.
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