Sentence examples for between model estimates of from inspiring English sources

The correlations between model estimates of the probability of survival and actual survival in the specified groupings are given in Table 6.

Even if the time period of data collection does not overlap, this data may be informative regarding the general relationship between model estimates versus in situ estimates of vegetation productivity.

Model performance was assessed statistically by splitting cases into training and testing sets of the same size, and clinically by investigating the clinical course details of about one quarter of the patients in whom the difference between model estimates and actual number of PRBC transfused was higher than the root mean squared error.

The TSMSM was run using fields of near-surface soil moisture from microwave imagery collected by aircraft on six days during the experiment, yielding a root mean square difference (RMSD) between model estimates and tower measurements of net radiation (Rn) and soil heat flux (G) of approximately 20 W m− 2, and 45 W m− 2 for sensible (H) and latent heating (LE).

Risk differences (RD) were computed as the difference between the model estimates of absolute risks of mortality in the presence and absence of heat wave for each modality of the considered covariates.

The statistics of the comparison between model estimates and observations show that the best results are obtained for the winter nitrate concentration (Fig.  3).

The difference between model estimates and observations is completely accounted for by natural variability and fits within the range of modeled uncertainty.

The inherent uncertainty of the EFSA Panel's approach is reflected in the exposure assessment and may explain the discrepancies between the EFSA model estimates of the dose distance relationship and our empirically based findings.

No significant associations were seen between lung function changes and the combined model estimates of Eag.

The model estimates of the relationships between various risk factors and mortality were robust, from including multiple confounding co variables in the models.

In this model, estimates of relative effects between non- reference/baseline treatments were assumed to be exchangeable across outcomes, which enabled estimates to be obtained for all outcomes by predicting effects where the interventions have not been considered for the particular outcome of interest.