Sentence examples for different regression models from inspiring English sources
The phrase "different regression models" is correct and usable in written English
You can use it when discussing various types of regression analysis in statistics or data science. Example: "In our study, we compared the results obtained from different regression models to determine which one provided the most accurate predictions."
Such healthier profile in moderate drinkers was not apparent in adolescents, and potential differences in background characteristics and health behaviours were adjusted for in different regression models.
However, this method does not take the dependency between the intermediate risk factors into account and moreover, it can transform each SNP variable differently; which makes it difficult to integrate the results of the different regression models.
Using five different regression models, we found that the impact on technology on well productivity is greatly over-estimated.
Different regression models were used to remove collinearity and spatial autocorrelation among selected variables.
The evidence is equivocal because we use a number of different regression models to deal with the uncertainties inherent in a large, cross-national panel dataset – unobserved country-level differences, or, to invoke a familiar phrase, "unknown unknowns".
In this study, to have an idea of geometric properties on ship motions of gulets three different regression models are developed.
This study develops a method that rationally compares different regression models and selects the most appropriate model for a specific site or deposit.
The relationship between the model parameters and the responses was analyzed by a calculation of two different regression models: one linear polynomial model and one model that includes interaction terms.
Moreover, to highlight robustness and precision of the addressed approaches, two different regression models have been developed and results obtained from the aforementioned intelligent models and regression approaches are compared with the corresponding refractive index data measured in laboratory.
Different regression models (classical and neural approaches) have been considered and a randomised resampling procedure has been designed in order to choose the best estimation model from a statistical point of view.
Hence, we have different regression models for different types of noises.
