Sentence examples for regularized data from inspiring English sources

Since James et. al. [2] suggest that there is a peak in rate of travel associated with departure from northern foraging areas, we fit a robust nonlinear smoother to the times series of successive daily distances traveled (as calculated from the regularized data).

What is the biological impact of extracting denoised (and regularized) data for 3D gene expression?

The resulting binned regularized data was extracted and for each protein was summed across wells by scaled Gaussian summation at the peak position and width of the log-scale time base.

Using BSML as a common output format has the added advantage of regularizing data by using terms from controlled vocabularies such as the Sequence Ontology (Eilbeck et al., 2005) and Gene Ontology (Ashburner et al., 2000).

"Going forward, cities, states, and businesses – all will need localized, regularized information delivered to them".

Having regularized our data and then calculated the observed deviations that we fit using our SSM (Equations (1) and (2)) we can now be more concise about the measurement error and process error distributions for this particular application.

This enables storing more relevant information from a single measurement as the data are interpolated and regularized in the data processing phase instead of during the measurement.

The easiest way on how to overcome this is to regularize the data back before analysis - now with the desired resolution that can be locally much larger than for the coarse image.

In order to regularize the data prior to fitting the curves, profiles of patients who discontinued during Weeks 2 7 of treatment were completed using the average of 50 imputed values generated with Bayesian regression fitted to the previous outcomes at every time point past the first week (SAS® PROC MI).

In order to explore the transcriptional and regulatory context of RNA DNA hybrid peaks, regression models were fitted to the data, regularized using the least absolute shrinkage and selection operator (LASSO; [ 66]) with the peak density as the response variable.

While the MTL and L 21 norm regularized MTL performs well with ideal data, the data may not always be represented ideally using a single structure.