And I would ban linear regression.
One of r's strengths is its ability to calculate linear, as well as nonlinear regression models.
This paper considers the estimation in the linear regression model under the criterion of minimizing the sum of absolute errors.
In addition, results of the linear regression for stress and instantaneous strain show that the instantaneous axial strain and axial load approximated to grow proportionally.
This paper first assort the topography of different district with the fuzzy classification, and then the expanding coefficient is gotten by the model of linear regression, so we can get more accurate information for the network planning.
Afterwards the results are analyzed through nonlinear regression in order to get the function between the amount of dust particles and time of vibration and vibration frequency.
simple linear regression
Simple linear regression is also a versatile modeling technique.
The linear regression equation on the relationship between peroxide content in acrylonitrile and PAN fiber yellowness was obtained by regression analysis.
The correlative coefficients of linear regression function for isochronous stress-strain curve are all higher than 0.
This study using linear regression model to examine if there are relations between independent and dependent variables, and the results indicate that two of these factors( interest coverage ratio and risk) have a significant association with the firm's discretionary accruals.
general linear regression model
classical normal linear regression model
These transformations can linearize the data so that simple linear regression can be used to model the data.
Method According to the theory of detecting outliers in linear regression analysis, the measured value of the samples in quality control was processed by EXCEL.
A kind of nonlinear regression estimator for limited Population is given and the quality and the sampling variance about is discussed.
Some problems on heteroscedasticity in multi-linear regression models;
To know preschooler's constitution and to study methods of making normal values of preschooler's physical exertion using linear regression model.
On the basis of our mathematic models of the titration, the content and conditional dissociation constant may be determined by using nonlinear regression.
The concentration factor (CF) and time (t) was linear regression relation.
Presents a robust estimate for the linear regression of sensor output characteristic based on the robustness of least absolute deviation estimate.
multiple normal linear regression mode
The linear regression model is used to calculate and measure the effect of investment to economic growth in regions of the Bohai, Yangtze River Delta, Pearl River Delta and the Central Region of China, and different degrees of investment dement in the interior of the four regions.
By using multivariate linear regression analysis, the mathematical model to classify and evaluate reservoir with well logging data was established.
Method Statistical methods of linear regression, multiple stepwised regression, two-way ANOVA were used to analysis the relation of TTS with audition, noise level, working-year and age.
To study the relation between the content of hemoglobin and calcium, iron and cuprum in children's blood, we use multiple linear regression analysis.
simple linear regression model
standard linear regression mode
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