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We consider the model of regression with random design, where the design density is unknown.
According to Orr [22], Marcek [18], the most used model of regression neural network type is the RBF neural network.
It takes regression model as the first stage to fit overall distribution of the original model, and then interpolation model of regression model approximation error is used as the second stage to improve accuracy.
the y i counts in area i, are independently identically Poisson distributed and have an expectation in area i of e i, the expected count, times θ i, the risk for area i. a logarithmic transformation (log(θ i )) allows a linear, additive model of regression terms (βx i ), along with.
All weather IMFs identified in single weather variable models were then selected in the final model of regression analysis (i.e., multiple weather variables model) to compute the most significant predictors of headache incidence.
The CTC and CEC changes were associated according to waveform model of regression analysis (R=0.67, P=0.05, Figure 3A).
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This method is based on a mixture model of regressions, the parameters of which are estimated using the EM algorithm.
Focusing on prognostic markers in oncology, they discuss issues of statistical model building in the framework of regression models and of classification and regression trees.
This review will outline the involvement of the different macrophage subsets throughout atherosclerosis progression and in models of regression.
The quantitative methods used included random effects models and fixed effects models of regression coefficients, odds ratios or hazard ratios.
Selective attrition and inappropriate modeling of regression toward the mean (RTM) are two potential sources of bias in such studies.
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examples of regression
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