Sentence examples for model knowing from inspiring English sources

If you've ever agonized over whether it's the right time to replace an old gadget with a spiffy new model — knowing that the new one may well become obsolete in a few months — you probably have an inkling of the kinds of decisions high-tech marketers must make in planning their products.

Wharton began the talk by defining the term "model," knowing that it can often times be rather ambiguous.

In 2017, we aggressively doubled our schedule, because we understood our business model knowing that volume was the one thing that was going to save us.

Cursory comparisons suggest that this model achieves accuracy comparable to or better than several commercial odds-makers, despite this model knowing nothing about teams, players, or strategies, and instead relying exclusively on the observed tempo and balance patterns in scoring events.

Others in my family may have been enamored by her stringency but have chosen a looser model, knowing that her self-imposed structure was way too monastic for them.

Simply speaking, since there are no mutations in the model, knowing the types present in the system initially reveals with certainty what will happen in the end.

While these peekaboo fabrics look all airy and ethereal parading down a runway on a reed-thin 17-year old-model, knowing how to wear any of them in real life isn't exactly obvious.

Malmquist bias sounds equivalent to missing data model: upon knowing a cosmological model (IMF or some mass distribution?), roughly one knows the proportion of observables, although I understand that the imf or some relevant indicators of the material universe are linked to the complexity of this bias.

Yamana explains that climate impact studies may be based on the climate predictions of a single model without knowing whether that model accurately represents the region of interest.

In summary, a wideband propagation model allows knowing some system characteristics, for example, the frequency selectivity, intersymbol interference, and error floor.

Technically, we maximized the likelihood of the model predictions knowing the data by assuming a Gaussian distribution of the model errors through the Nelder-Mead algorithm implemented within the optim package in R28 (Supplementary Materials S3).