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Pneumatic gauging involves the determination of estimates of dimensional deviations from measurement experiments using a valid gauge model.
The essence of the current situation is the fitting of the multiplicative model (2) to given experimental data, which reduces to the determination of estimates for the four parameters α, β, a, b.
The third step in the implementation of the algorithm is the determination of estimates α 2 and β 2 for α and β using the model lnleft{ln N t) - ln N_{0}+a_{1}t^{b_{1}}right}=ln alpha +betaln t. (18).
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Consequently, the first step in the implementation of the algorithm is the determination of initial estimates α 1 and β 1 for α and β using the model ln{ln N t) - ln N_{0}}=ln alpha +betaln t. (14).
The second step in the implementation of the algorithm is the determination of initial estimates a 1 and b 1 for a and b using the model lnleft{-ln N t) +ln N_{0}+alpha_{1} t^{beta_{1}}right}=ln a +bln t. (16).
One potential advantage of this method is that determination of optimal estimates is less computationally intensive than the LRTS procedure documented in this work.
Following a descriptive analysis using cross-tabulation and distribution of single variables, linear and logistic regression analysis was used for determination of effect estimates.
For each animal, the data from both sections were therefore pooled for determination of average estimates of lesion densities and pixel counts per kidney.
The determination of population estimates for restrictive ventilatory defect (RVD) within populations exposed to mining dusts typically relies upon the use of chest X-ray (CXR) and spirometry.
Previous correlations showed very low coefficient of determination of the estimated TOC compared to the actual laboratory data.
The Pearson correlation was used to examine the accuracy of ultrasonographic determination of the estimated fetal weight.
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