One possible explanation for these finding might be a type 2 error because of a too small sample size.
A too small value will not be enlarged, but instead it generates an error that will spread throughout the domain.
An appropriate choice has to establish a good trade-off between estimation errors due to instationarity and inaccuracy due to a too small number of samples.
A Cox-model, however, provides too small standard errors and hence confidence intervals that are too tight as reflected by the low coverage probability.
In general, our results obtained both in the context of simulated and real interictal epileptic spikes suggest that 2T-EMD should be preferred for the denoising of low SNR data but that the reconstructed data would most likely lead too (small) localization errors.
This would, in turn, give rise to biased estimates of herd-level independent variables and too small standard errors.
Even if you see a small error like the letter "a" has it's line too long, correct the child immediately.
If the observed noise variance is too small, its estimation error may be too large to valid the estimate.
On any other day, such a small error would be inconsequential.
It is important not to get too hyped in the search, remember that if an error is too small then the value of the coin is not too much.
