Examples of PolynomialRegression

de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression

A polynomial fit is a specific type of multiple regression. The simple regression model (a first-order polynomial) can be trivially extended to higher orders.

The regression model y = b0 + b1*x + b2*x^2 + ... + bp*x^p + e is a system of polynomial equations of order p with polynomial coefficients { b0 ... bp}. The model can be expressed using data matrix x, target vector y and parameter vector ?. The ith row of X and Y will contain the x and y value for the ith data sample.

The variables will be transformed in the following way: x=> x1, ..., x^p => xp Then the model can be written as a multiple linear equation model: y = b0 + b1*x1 + b2*x2 + ... + bp*xp + e @author Elke Achtert

        x.set(k, k + k_0);
        y.set(k, knnDistances.get(k + k_0).doubleValue());
      }
    }


    PolynomialRegression regression = new PolynomialRegression(y, x, p);
    PolynomialApproximation approximation = new PolynomialApproximation(regression.getEstimatedCoefficients().getArrayCopy());


    if(logger.isDebugging()) {
      msg.append("approximation ").append(approximation);
      logger.debugFine(msg.toString());
    }

        x.set(k, k + k_0);
        y.set(k, knnDistances.get(k + k_0).doubleValue());
      }
    }


    PolynomialRegression regression = new PolynomialRegression(y, x, p);
    PolynomialApproximation approximation = new PolynomialApproximation(regression.getEstimatedCoefficients().getArrayCopy());


    if(logger.isDebugging()) {
      msg.append("approximation ").append(approximation);
      logger.debugFine(msg.toString());
    }

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Examples of PolynomialRegression

Examples of de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression

Examples of de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression