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As a criterion of goodness of fit, the sum of squares error function was used: f k j, K j = ∑ i n v i − v ¯ i 2 Where n is the total number of experimental points, v i ¯ is the experimentally measured value of the variable or reaction rate, v i is the corresponding value estimated from the model, k j, K j are unknown parameters.
As a criterion of fitness, the following function was used: (33) f k j, K j, = ∑ i n v i − v ¯ i 2 Here, n is the total number of experimental points, i v ¯ is the experimentally measured value of the variable or reaction rate, v i is the value of the variable or reaction rate calculated based on the model at a point corresponding to the experimental ones.
Number of experimental points.
Precision increases with the number of experimental points.
Upon using HRS a structured arrangement of experimental points in the virtual holograms was observed.
Therefore, in this study, the control point of experimental points is constructed.
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We chose theoretical calculation as the determination of experimental point-spread functions can be unreliable for thick specimen, like whole-tissue samples [ 24].
The issue of experimental-point fitting has been addressed by Glatting and coll in blood serum dosimetry [ 2], where collecting several data (generally three) for each kinetic phase is feasible from the cost point of view.
With number of degrees of freedom of 11 (29 experimental points and 18 essential parameters), the value of Q was 1.42·10-11.
However, and in many situations, maximum precision is attained when sampling consists of replicates of specific experimental points.
The confidence of different models generated by Doehlert designs is studied by means of the uncertainty of the experimental points.
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