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R

regression(double[][], double[]) - Method in class models.LeastSquare_Regression
A default constructor for regression where the intercept (constant) is assumed to be included.
regression(double[][], double[], boolean) - Method in class models.LeastSquare_Regression
This the main method of this class that will compute the most important OLS regression statistics such as the : Beta Anova R and R-Squared T-statistics for the predictors Beat standard errors T Pvalues and more
regression(double[][], double[], boolean, double, int) - Method in class models.Logistic_Regression
This is the main Newton-Raphson method for Logistic Regression
regression(double[][], double[]) - Method in class models.Logistic_Regression
A constructor of logistic regression for faster execution.
regression(double[][], double[], double, int) - Method in class models.Logistic_Regression
A constructor of logistic regression for faster execution, where we put an intercept
regression(double[][], String[], double, int) - Method in class models.Multinomial_Logistic_Regression
This is the main method that will compute the coefficients and all other stats for the Multinomial Logistic model.
regression(double[][], String[]) - Method in class models.Multinomial_Logistic_Regression
A simpler constructor of Multinomial Logistic Regression.
removeElement(int) - Method in class Assisted_Classes.DescriptiveStatistics
This method removes an element from the current instance of DescriptiveStatistics
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