Examples of org.jamesii.core.math.regression.MultivariateLinearRegressionLeastSquares

org.jamesii.core.math.regression.MultivariateLinearRegressionLeastSquares

kipedia.org/wiki/Ordinary_least_squares Algorithm: vector_of_coefficients = Inv(XT*X)*XT*Y X - Matrix of input variables. XT - X transposed. Inv() - calculate the inverse matrix. Y - vector of output variables. Note: the input matrix X must have full column rank, i.e. the columns of this matrix must be linearly independent! Note: To calculate the standard error for each coefficient a matrix already used to calculate the coefficients is needed. Therefore this implementation stores a possibly huge matrix after getCoefficients() until getStandardErrorForEachCoefficient() is called. @author Rene Schulz

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public class TestMultivariateLinearRegressionLeastSquares extends
    AbstractTestMultivariateLinearRegression {


  public TestMultivariateLinearRegressionLeastSquares() {
    reg = new MultivariateLinearRegressionLeastSquares();
  }

Related Classes of org.jamesii.core.math.regression.MultivariateLinearRegressionLeastSquares

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