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Compared to the method of Reddy and Raj, our method performs comparably at 0 dB but significantly better at other input SNRs.
Our numerical experiments, carried out for two-dimensional elliptic problems, reveal that the Conjugate gradient algorithm is the most efficient option, while the Eyre Milton method performs comparably to the Chebyshev semi-iteration.
We compare the performance of our approach to a recently proposed method based on quantile regression, and demonstrate that our method performs comparably to this approach in terms of two widely used methods for assessing the quality of probabilistic scenarios: the Energy score and the Variogram score.
Simulation studies show that the proposed method performs comparably to existing competitors when n is moderate or large, but it is better when n is small.
Our tests demonstrate that our method performs comparably to MEME in cross-validation.
They show that their consecutive sampling method performs comparably to these methods, in terms of identifying similar sets of differentially expressed genes, and also shows more consistency.
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Though requiring no previous assumptions about the detailed shape of the cortex or other brain structures, the method performed comparably (sensitivity = 0.91) to direct cortical thickness estimation techniques (sensitivity = 0.93) at separating populations in a data set designed specifically to test the cortical thickness estimation algorithms.
In addition, our method performed comparably to competing methods, including Dynamic Bayesian Networks, on simulated data from the DREAM4 challenge, even in the absence of prior information.
For the DREAM4 data, for which no prior information was available, our method performed comparably to other methods, while producing more compact networks.
In our study, the Vidas SLM method performed comparably to the NMKL method (Table 1), giving slightly better results for pig faeces and slightly poorer results for cattle and poultry faeces.
For more realistic sampling, the weighted residual methods performed comparably to the other two.
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