Examples of using Regression models in English and their translations into Russian
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Emission projections were based on standard regression models, without the use of macroeconomic
During the courses I learned to estimate multilevel logistic regression models, which are especially important in improving the project on predictors of national pride that I am currently working on.
Fast estimation of parameters is achieved with introduction of additional filtered linear regression models for each parameter of the signal.
The revealed levels of communication will allow developing regression models and nomograms of the forecast of the sizes of organs of the abdominal cavity depending on somatometric indicators with sufficient information capacity.
Firm-level studies are based on analysis(usually based on econometric regression models) of data at the individual firm level.
The article offers regression models which describe indicators of trade export
as well as alternative regression models based on bridge regression
This entails calculating regression models each period and using the resulting parameter estimates to predict the price of every item based on its characteristics.
The regression models are run separately for males and females at UN subregional level 3
We use multi-level regression models and World Values Survey(WVS)
I could have made some sexy regression models, could have gotten permission from Admin to get that deluxe bagel and lox spread we sometimes get;
Apparel economists now rely more on their commodity knowledge to develop regression models.
Survey of HSE and fixed effects regression models.
that have unusable information are imputed using regression models.
Theil-Sen estimation has been applied to astronomy due to its ability to handle censored regression models.
these can be introduced in simple regression models or sophisticated numerical models for film-thickness calculations like any other EHL contact fig.
Unlike most previous studies, we have tested not only static regression models(multifactor linear regressions)
For example, the simplest linear regression models assume a linear relationship between the expected value of Y(the response variable to be predicted) and each independent variable when the other
assessing the impact of each variable in the model- were used for each of the regression models.