Примеры использования Parameter estimates на Английском языке и их переводы на Русский язык
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Fiber parameter estimates seem to fluctuate the most.
Flexible Wald, likelihood-ratio, andscore tests for parameter estimates.
Parameter estimates from these countries have proven to be more stable than others.
As expected, the standard errors for most parameter estimates notably increased.
The parameter estimates may thus be unstable, particularly as new data are added.
Over the years it even appears that the parameter estimates themselves have become more stable.
The parameter estimates are confounded and are likely to be unstable, particularly as new data are added.
The validity of this assumption is unknown, butit is thought that the parameter estimates are conservative.
The longline parameter estimates for these time periods were used in the revised stock assessment for.
Mr Russell Leaper Many ecosystem models have placed an emphasis on parameter estimates rather than model structure.
However, the parameter estimates in the fiber only model varied widely between the models.
For this type of approach it is more critical to put broad bounds on all the pathways rather than refine parameter estimates for a few.
Any parameter estimates that conflict with a priori expectations are further investigated until they are explained.
By not including these important variables the minimally cleaned model is misspecified and therefore the parameter estimates are biased.
Only variables with parameter estimates significant at the 5 percent level are actually used for quality adjustments.
Not all regression models were used for quality adjustments and some were used only for short time periods since parameter estimates were believed to be unstable.
The parameter estimates are less precise due to an increase in the standard errors for almost all of the parameter estimates. .
Contrary to the minimally cleaned data set model, none of the parameter estimates switched ranks within their categories between the two models.
Parameter estimates for fiber are thought to be the most commonly used parameter estimates for quality adjustments.
However, there are enough instances where the parameter estimates do change drastically to indicate that the models are not stable over time.
Parameter estimates from highly correlated variables are not used for quality adjustments since multicollinearity causes parameter estimates to be imprecise.
Simply comparing models for several items showed that the parameter estimates for the brand category variables are nearly the same for the same item over different time periods.
Italian made shoes and clothing have long been recognized as having unsurpassed quality and the models that include Italy(or in some cases the Western Europe region)as a variable have supported this belief by their positive, significant parameter estimates.
Prior to using the parameter estimates from a regression model to quality adjust substitutions, the overall quality of the model is evaluated.
The resulting model is still quite good according to the adjusted R2(.7489), but seven of the parameter estimates that are significant in the"final" model are no longer significant.
Most of the parameter estimates still made sense; in other words, the signs remained the same and usually the parameter estimates' rank within a category did not change.
Another method of gauging stability of the parameter estimates is to simply compare parameter estimates from the same model from different time periods.
Often the parameter estimates are nearly identical and(provided the base variable does not change) the sign of the parameter estimate is almost always the same.
The modeler verifies that the signs associated with the parameter estimates are in the expected direction and that the ranks of the parameter estimates match a priori expectations.
Only two of the parameter estimates that are significant in the final model are no longer significant and one parameter estimate became significant in the all variable model.