Sentence examples for model precision was from inspiring English sources

The simulations reflected the variation trend of observations well but the model precision was poor.

Model precision was determined using the coefficient of determination (R2) and the root mean square error (RMSE).

Model precision was determined through examination of the root mean square error (RMSE) and coefficient of determination (R 2).

Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was very high.

Model precision was assessed for parametric and non-parametric models from the validation dataset using the squared Pearson correlation coefficient (R 2) and root mean square error (RMSE).

In mixed conifer forest in Washington state, USA, model precision was more affected by sample plot size than pulse density [39].

The parameters of principal importance for the model precision are identified and a procedure for their estimation is proposed.

The effects of time interval of MDBNs, common cause weight, imperfect proof test and repair on model precision are researched.

Note that model precision is not given for use of LiDAR without age (panel a) as these models are not feasible.

Model precision is based on the ability to fit a relationship between predicted and empirically observed activities (namely the Pearson correlation or R fit of the model between predicted and observed).

By contrast, assessments of the implications of observation error (arising from sampling limitations) for model precision are often lacking, but see [6], [7], perhaps due to a widespread acknowledgement of the ubiquity of sampling constraints [8].