Sentence examples for maximization option from inspiring English sources

Analysis of the case/pseudocontrol dataset in UNPHASED (using the default maximization option) was relatively fast, taking around 12 h to process the longest chromosomes and producing a total of 875 MB of output files.

We found this problem in UNPHASED could be avoided by use of the slower (Nelder-Mead) maximization option, however, this option was not feasible on a genome-wide scale; we estimated that the analysis would have taken several months to run on our system, even when divided into 22 (or more) parallel jobs.

Finally, our decision theory culminates in the following norm: Expected Utility Maximization Choose the option with the highest expected utility.

In the broad class of alternative-based choice models, choices among options are presumed to be guided by a principle of value maximization [14]; i.e., the options are independently assigned an overall value, these values are compared, and the option with the highest value is chosen [15], [16].

Proprietary algorithms help users to establish bid-to-position, target ROAS, or ROI maximization – and then use defined options and parameters define the rules they want applied at the ad group or keyword level.

As a consequence, options that allow maximization of the data obtained from a single sample are highly valued.

Principles of nonconditional expected-utility maximization use the same information for all options, and hence exclude information about an option's realization.

The expectation-maximization (EM) and "droprare" options were used.

Profitability maximization in the case of sequential sampling of multiple options relies on sensation (converting a physical stimulus into a neuronal firing pattern), memory (maintaining a representation of a physical stimulus over a period of time), and decision-making (comparing representations from different sources and performing a motor task based on the results of this comparison).

According to the normative concept of expected utility maximization [19], derived from the expected utility model of Daniel Bernoulli, people should choose the option that gives the highest expected utility.

E-R analyses often use the software NONMEM with the LAPLACIAN approximation option, although more advanced estimation options such as the stochastic approximation expectation-maximization (SAEM) and importance sampling (IMP) have recently been included.