Sentence examples for closeness of model from inspiring English sources
The model of best fit was selected for each subject by two independent statisticians blinded to treatment group based on a set of pre-defined evaluation criteria: possible data errors; outliers affecting model fit and whether to exclude them; estimated modeled baseline and fit of model in baseline region; estimate of PC90 and fit in these regions; and closeness of model fit with observed data.
Moreover, the absence of clear demarcation between model and non model with reference to distance (closeness of model and non model) may have created information contamination as well as diarrheal disease transmission to the model HH members and vice versa.
All of these results are consistent with the closeness of the model and data traces in Fig. 6.
The mean standard error (MSE) and the mean absolute error (MAE) were used as measures of closeness of the model to the actual system.
Results:We develop a new measure that balances GDT_TS reward for the closeness of equivalent model and target residues ('attraction' term) with the penalty for the closeness of non-equivalent residues ('repulsion' term).
Closeness of a model to the data can be measured by relative enthropy (also called Kullback‐Leibler distance) between two distributions p= P(X| G) and q= P(X| G′) [ 104]: (8) D (p ∥ q ) = - ∑ x p (x ) · log q (x ) p (x ), (9) D (p ∥ q ) = - ∑ x p (x ) · log q (x ) + ∑ x p (x ) · log p (x ).
In general, this cut-off value can be set according to the desired closeness of the reduced model to the original.
The closeness of the hypothetical model of PQLI to the empirical data of interviewing rating scores is evaluated statistically through gamma test [ 20].
The Kullback Leibler Information Criterion (KLIC) (Kullback 1959) measures the closeness of a probability model to the true distribution of data.
These schemes weight parameters according to the closeness of a forward simulation of a model (such as those produced by STI-GMaS) to true data, allowing for good parameter estimation even in the presence of extremely complicated disease dynamics.
Unfortunately due to unavailability of data regarding mobility of users on the landscape we were not able to test closeness of the proposed mobility model and empirical data.
