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Furthermore, we counted the cases in which the real parameter values fell within a single standard error from the average inferred parameters.
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The presented results are evaluated by the estimated root mean square error (RMSE) from the average results of 500 independent Monte Carlo simulations.
It should be noted that the positioning error estimated from the standard deviation of repeated pass-through measurement is not absolute error but deviation from the average measurement at each position.
In each panel, yearly mean value and its error are deduced from the average and dispersion of monthly mean values.
Standard error was computed from the average of the ΔCT values for each biological sample [ 70].
For simple singing, we calculated the average error from the target note (vocal accuracy measured in cents) and average vocal stability (i.e., average of standard deviations across trials in cents – smaller standard deviations reflect greater vocal stability), and used these measures as dependent variables.
As indicated by the high error rates, the average network reconstruction from this data sets is very poor.
The error rates are reported from the average of 100 repeats of the random missing procedure for the missing rates at 0.1%, 0.5%, 1%, and 5%.
Note that the variability around the mean values may result from alignment errors from the subtomogram averaging.
Where the missing distances are set with largest distances, the tolerance to the level of missing distances is significantly lower as the error from the furthest node increases the average error.
Shorter traces were also proportionally extended based on the average error from the run-off traces.
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