Sentence examples for data-driven estimates from inspiring English sources
In states across the country, data-driven estimates of the risk of recidivism are being used to set jail sentences.
Quantifiable safety, mobility, and environmental benefit projections such as data-driven estimates of how the project will improve the region's transportation system efficiency and reduce traffic congestion.
Inference 122, 229 252] the robust selectors lead to robust data-driven estimates of both the regression function and the regression parameter.
SloVAR obtains flexible, data-driven estimates of effective connectivity and hence is useful for building connectivity models when prior information on dynamic regional relationships is sparse.
The Global Burden of Diseases, Injuries and Risk Factors (GBD 2010) Study was designed to address such analytical shortfalls by delivering data-driven estimates of epidemiological parameters for nearly 200 diseases and injuries, including the primary cardiomyopathies.
Instead of using purely data-driven estimate methods, we propose a new estimate method to select the optimal number of clusters by incorporating gene functional category information.
Similar statistical models were utilized to estimate associations between expression levels and GDM, adjusting for the same covariates used in our methylation models and our data-driven estimated surrogates for batch and ethnicity (Additional file 1: Table S8; top 20 unique coding genes, sorted by significance).
The second was data-driven and estimated the optimal time of change (τ ^ 1 ) under a 2-piece exponential model, for example, to address up to what time point would a hypothetical intervention be useful.
Since we have a data-driven, realistic estimate of the distribution of litter sizes, we can explore the consequences of making the Poisson assumption, and we find that, in this instance, the Poisson assumption appears reasonable.
Overall significance and P-values associated with each data-driven effect were estimated by permutation tests, whereas effect size was estimated as the proportion of cross-block covariance accounted for by the latent variable.
This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data.
