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The relationship between the error distribution and the raw track quality suggests that our model may provide even better accuracy with tracks of higher quality.
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We suspect, however, that interactions between the error distributions embedded in satellite data products and the models and assumptions underlying their ecological and biophysical applications may be commonplace.
This method of non-linear regression involves the step of minimizing the error distribution between the experimental equilibrium data and predicted isotherm (Krishni et al. 2014).
The differences of the error distribution between both single DNA-pools varied only marginally.
The difference between A and B based on the error distribution of d(a i, B) and d(b j, A) was evaluated.
The models (for each plate and for each type of error) explained between 14.32% and 37.38% of the error distribution and were highly significant (P < 2 × 10-16).
There is a significant difference between the means of the error distributions of SVR with linear/RBF kernel, and GPR with linear/squared exponential covariance function, as shown in Figure 4.
To assess the effect of different ranging distances (i.e. variable footprint size) on DTM error across the study area, the control points were grouped into submontane and montane elevational classes, and the error distributions between the groups were compared.
Figure 12 Symmetry of the error distributions.
The error distributions involve families of skew-normal distributions.
A comparison between the cumulative error distribution function of the described system and that of our earlier proposed system [15], evaluated on the same test bench and obtained with the three best speakers, is presented in Figure 15.
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