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The relative errors of the data were about 3%.
Then, a perfect matching between data and model is useless when the errors of the data are comparably large or small.
However, this characterization is meaningless if the errors of the data σ f i i = 1 N are either (i) quite larger than their deviations from the model values, i.e., if σ fi > > |f i - V(x i ; α)|, or (ii) quite smaller, i.e., if σ fi < < |f i - V(x i ; α)| (e.g., see Figure 3).
This bootstrap method produced a sample of projected cubic-spline curves that inherits the temporal biases and systematic errors of the data.
Such artifacts might indicate sampling errors of the data in Additional file 4. Compare the evolutionary scenario designs defined in Methods.
The time interval between the delivery of forms and computerization of the data is kept as short as possible for two reasons: i) to reduce the chance of the data forms being lost and ii) to quickly resolve any errors of the data in the field.
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Payscale says the margin of error on the data is 10percentt.
Next, the weights matrix W is computed by minimizing the reconstruction error of the data point from its neighbors.
We measured the error of the data collection and subsequent numerical analysis and found the error for computation to be within 0.3%.
It is well-known that such a system is ill-conditioned and its solution is highly dependent on the error of the data.
Hence, predictive models should be assessed through: the analysis of the experimental error of the data, the evaluation of the models AD as well as the definition of intervals of confidence for the predictions.
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