Sentence examples for model variance as from inspiring English sources

For all prevalence categories, the total number of pinyon mice and total number of kangaroo rats appeared to have a strong influence on overall model variance, as these species segregated independently from all other species at all levels of prevalence.

These methods model variance as a function of intensity, and assume independence of probe sets.

Alemu et al. applied local polynomial likelihood estimation [ 31] to model variance as a function of the mean of expression.

The whole set of predictors explained 32.0% of the model variance as suggested by Nagelkerke R-square value.

When the metabolic syndrome replaced all risk factors (apart from age), it too was independently associated with ischaemic ECG in men and women and explained the same amount of the model variance as the individual CVD risk factors.

As before, the metabolic syndrome accounted for similar model variance as individual risk factors, was an independent predictor in both genders, and had an equivalent impact in men (OR = 1.22 (95% CI 1.01 to 1.49)) and women (OR = 1.21 (95% CI 1.02 to 1.44)).

Using hierarchical Bayesian model averaging (BMA), this study shows that segregating different uncertain model components through a BMA tree of posterior model probability, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool.

However, this interval still has some disadvantages: (i) it is hard to use when at least one leverage value is high; (ii) many iterations tend to be required to obtain the estimators of one global model variance parameter as the number of areas, m, increases, due to the area-specific adjustment factor.

In our model, variances are estimated as follows: (15).

Finally, the model captures the local desired signal variance, as well as the noise variance of each observed pixel.

Allowing for variance heterogeneity (i.e., model the variance as a function) in only the additive genetic variance would lead to a bias in the relevant parameter estimate because it is possible in theory for there to be heterogeneity in the residual environmental variance as well.