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Finally, our method performs about as well as surrogate variable analysis (SVA) when technical error is of large magnitude, and better than SVA when technical error is of smaller (but still realistic) magnitude.
However, WAVELET method performs about 37% better than TRUST and 29% better than HHrepID in sensitivity at FPR of 8%.
Since the method proposed in this work is greatly simplified as compared to the previously developed method, it is no surprise that the new method performs about four times faster.
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However, we noticed that the two methods performed about equally well.
The other four methods perform about equally well in the Osmotic shock response data set, but in the DNA damage data set our methods outperform HMoF as well.
This suggests that the methods performed about the same in the forecasting of seasonal epidemics.
Simulations for both noiseless and noisy mixtures indicate that the proposed algorithms have superior finite-sample performance in data-starved scenarios as compared to existing complex ICA methods while performing about as well as the best of these techniques for larger data-record lengths.
Compare agreement between a PEEP titration Method performed fast (about 7 minutes) and slow (about 45 minutes).
However, our probabilistic method performs better for small values of false positives (about <0.2).
Using only the most likely Gaussian pair for estimation, the MAP method is more efficient than the MMSE method but performs about 0.1 dB worse.
2. When noise increased to a large extent, the proposed method was able to perform about twice as well as random walk approach did.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com