Exemplos de uso de A linear regression model em Inglês e suas traduções para o Português
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The estimation of this model is based on a linear regression model in which.
is a technique for estimating the unknown parameters in a linear regression model.
The evaluation of behavioral variables was done with a linear regression model incorporating information on survey weights
is a type of linear least squares method for estimating the unknown parameters in a linear regression model.
A linear regression model was developed for the Hg variation and Poisson regression models with a robust variation were adjusted for the anemia and severe anemia variables.
In this study and in previous researches by different authors, it was note found a linear regression model associating bite force
The age which will have the 1000 points maximal corresponding to the absolute national record obtained is calculated through a linear regression model, in the 5 known data pairs age and punctuation;
The results of the SFI were compared between the groups using a linear regression model with mixed effects random and fixed effects, at the significance level of 5% p>0.05, employing SAS® 9.0 software and R software.
again needed to be adjusted to a Linear Regression Model.
it didn't find a linear regression model with at least two of the studied variables,
nerve are independent, a linear regression model was proposed for each of the risks,
relating external and internal criteria through a linear regression model applied on the results of partitioning and density-based clustering algorithms. each algorithm was run over synthetic datasets generated for this purpose, using different configurati.
following a linear regression model; the presence of active photosynthetic leaves, following a quadratic regression. .
estimate the potential value of the main energy sources of biomass produced annually in northeastern brazil,(2) set a linear regression model for estimating biomass burning in areas of caatinga from satellite images,
To analyze multiple correlations, a multiple linear regression model was used.
The evaluation of the proposed correlation is given by applying a multiple linear regression model.
If we have a simple linear regression model, we have some equation like Y=A1X1+A2X2. Plus.