Sentence examples for using the coefficients estimated from inspiring English sources

The prediction of the model was improved using the coefficients estimated here with physiologically relevant units.

Using the coefficients estimated from the regression model developed on the learning set, a predicted score was calculated for each subject in the evaluation set for every number of FOVs.

The second step is to use the coefficients estimated from the diffusion scheme of analogous service.

Specifically, we used the coefficients estimated from the derivation model to predict the log-odds of mortality in the validation cohorts.

In the analysis by histology, we defined the standard Wald chi-square test statistic using the coefficient estimates derived from a polytomous logistic regression (where the response variable was coded on four levels: controls, adenocarcinoma cases, squamous cells carcinoma cases, and small cells carcinoma cases) and the covariance matrix of the coefficients.

Using the coefficient estimates, rather than IRRs, we can determine that the turning point is approximately 79 years where age and chronic disease develop into a negative relationship.

If we use the coefficient estimated in Eq. (1) from Table 3 (0.038), the total cumulative bias reaches 59.5%, which is very similar to the 61% from Table 3.

For the k-parameter, calculated using the coefficient estimate of Open image in new window (see Eq. 5), a higher value implies a more concave function and a value close to zero implies an almost linear relationship between the noise level and the property price.

where the matrices S ̃ ⌣ ∈ ℂ J × ( N - P ) and X ̃ ⌣ 0 ∈ ℂ J × ( N - P ) consist of the temporally whitened versions of { x ( n ) } n = P N - 1 and { s ( n ) } n = P N - 1, respectively, using the coefficient estimate A ^ NSCM H.

We predicted the probability of obesity using the coefficient estimates from the final reduced model (Supplementary Table 2), converted from odds to probabilities, across the observed range of food environment scores and graphed the results.

In the second stage we used a multivariate weighted regression model using the coefficient estimates from the first stage as the dependent variables and the variance-covariance matrix of these coefficients as weights.