Sentence examples for more efficient statistical from inspiring English sources

Results presented in this paper can be beneficial for the traffic smoothing improvement and for the design of more efficient statistical multiplexing.

The quantities of data involved and the non-linear complexity of the models involved are difficult to implement with more efficient statistical sampling regimes such as Gibb's sampling.

Grisedale and van Daal [17] favour use of a single run, but their comparison was with a consensus sequence obtained from multiple replicates, rather than the more efficient statistical analysis available through analysing individual replicates.

To name a few, pathway-based analysis of NGS data requires more efficient statistical methods for detecting genome-wide rare variants, good computational capacity for handling large-scale datasets, improved genotype calling rate for sequencing data and finally the precise functional annotations.

This technique is based on the linearization of transport equations and it is computationally much more efficient then purely "statistical" methods that are based on the simulation of a large number of devices with different doping realizations.

Among many challenges this application holds; development of more efficient and robust statistical methodologies with higher power to detect an association with a single marker has been one of the most important statistical issues, given that effects of individual markers are usually characterized as being small to moderate.

The adaptive scheme was more efficient than all other statistical methods for both parameters.

Simulation results demonstrate that the proposed ABC based method is more efficient in computation and statistical performance than other ML-based DOA estimation methods.

In most cases, orthogonal arrays are more efficient when compared to many other statistical designs.

As our processing capabilities grow in availability, and our algorithms and statistical tools become more efficient, so-called "training" time for machine learning is decreasing.

In the present paper an alternative solution is based on the development of two more efficient techniques to predict the relevant statistical moments of the dock response.