Sentence examples for using the mean parameter from inspiring English sources

In addition, the costs for all the experiments using the mean parameter values, (bar{theta }), are shown.

This produced the same pattern of results as was found using the mean parameter estimates reported below (see Supplementary Material).

On the basis of this deterministic approach (using the mean parameter values) overall healthcare costs for a patient receiving Mezavant were 624 Euro lower than for a patient receiving Asacol over a 5-year time period.

A single subject was simulated for each inhibition type using the mean parameters and the Kin, Kic, and Km calculated using the BIM binding model.

This run included a preliminary step of estimating the optimal noise-model parameters for a subset of 20 384 flowgrams, using a greedy algorithm, computing the mean intercept and trend and running the Viterbi on the entire dataset using the mean parameters.

To correct for this, when using the logistic prior, we suggest estimating the variational parameters with multiple random restarts and using the mean of the parameters corresponding to the top five values of LLBO.

One way sensitivity analyses were calculated using the mean values of each parameter, and varying the values of one parameter at a time.

After doing this for each child in a sample, it is possible to estimate a mean-constant curve using the mean values of the parameter estimates, thereby characterizing average growth in the sample.

Using the mean diagonal coupling interval parameter we described previously [ 27] we could divide these dogs into sub-groups with either normal or abnormal coordination in the sagittal ('x') plane and ask the question whether there was a concomitant alteration in the variability of lateral foot placement during recovery of locomotion.

To compare the performance of the three models, we obtain the predicted values for the test dataset using the mean estimations of the parameters from the posterior samples for all three models.

Thus, given the input test data Xtest (normalized by using the mean and standard deviation parameters obtained for the training set), the output test data Ytest (offset by the mean of Y) is predicted as: (12) Y test, pred = X test.