How to use

sumOfMeanDifferences

method

in

org.canova.api.util.MathUtils

/**
 * This returns the minimized loss values for a given vector.
 * It is assumed that  the x, y pairs are at
 * vector[i], vector[i+1]
 *
 * @param vector the vector of numbers to getFromOrigin the weights for
 * @return a double array with w_0 and w_1 are the associated indices.
 */
public static double[] weightsFor(List<Double> vector) {
 /* split coordinate system */
 List<double[]> coords = coordSplit(vector);
   /* x vals */
 double[] x = coords.get(0);
   /* y vals */
 double[] y = coords.get(1);
 double meanX = sum(x) / x.length;
 double meanY = sum(y) / y.length;
 double sumOfMeanDifferences = sumOfMeanDifferences(x, y);
 double xDifferenceOfMean = sumOfMeanDifferencesOnePoint(x);
 double w_1 = sumOfMeanDifferences / xDifferenceOfMean;
 double w_0 = meanY - (w_1) * meanX;
 //double w_1=(n*sumOfProducts(x,y) - sum(x) * sum(y))/(n*sumOfSquares(x) - Math.pow(sum(x),2));
 //	double w_0=(sum(y) - (w_1 * sum(x)))/n;
 double[] ret = new double[vector.size()];
 ret[0] = w_0;
 ret[1] = w_1;
 return ret;
}//end weightsFor

/**
 * This returns the minimized loss values for a given vector.
 * It is assumed that  the x, y pairs are at
 * vector[i], vector[i+1]
 *
 * @param vector the vector of numbers to getFromOrigin the weights for
 * @return a double array with w_0 and w_1 are the associated indices.
 */
public static double[] weightsFor(double[] vector) {
   /* split coordinate system */
 List<double[]> coords = coordSplit(vector);
   /* x vals */
 double[] x = coords.get(0);
   /* y vals */
 double[] y = coords.get(1);
 double meanX = sum(x) / x.length;
 double meanY = sum(y) / y.length;
 double sumOfMeanDifferences = sumOfMeanDifferences(x, y);
 double xDifferenceOfMean = sumOfMeanDifferencesOnePoint(x);
 double w_1 = sumOfMeanDifferences / xDifferenceOfMean;
 double w_0 = meanY - (w_1) * meanX;
 double[] ret = new double[vector.length];
 ret[0] = w_0;
 ret[1] = w_1;
 return ret;
}//end weightsFor

/**
 * This returns the minimized loss values for a given vector.
 * It is assumed that  the x, y pairs are at
 * vector[i], vector[i+1]
 * @param vector the vector of numbers to getFromOrigin the weights for
 * @return a double array with w_0 and w_1 are the associated indices.
 */
public static double[] weightsFor(double[] vector) {
  /* split coordinate system */
  List<double[]> coords=coordSplit(vector);
  /* x vals */
  double[] x=coords.get(0);
  /* y vals */
  double[] y=coords.get(1);
  double meanX=sum(x)/x.length;
  double meanY=sum(y)/y.length;
  double sumOfMeanDifferences=sumOfMeanDifferences(x,y);
  double xDifferenceOfMean=sumOfMeanDifferencesOnePoint(x);
  double w_1=sumOfMeanDifferences/xDifferenceOfMean;
  double w_0=meanY  - (w_1) * meanX;
  double[] ret = new double[vector.length];
  ret[0]=w_0;
  ret[1]=w_1;
  return ret;
}//end weightsFor

/**
 * This returns the minimized loss values for a given vector.
 * It is assumed that  the x, y pairs are at
 * vector[i], vector[i+1]
 * @param vector the vector of numbers to getFromOrigin the weights for
 * @return a double array with w_0 and w_1 are the associated indices.
 */
public static double[] weightsFor(List<Double> vector) {
  /* split coordinate system */
  List<double[]> coords=coordSplit(vector);
  /* x vals */
  double[] x=coords.get(0);
  /* y vals */
  double[] y=coords.get(1);
  double meanX=sum(x)/x.length;
  double meanY=sum(y)/y.length;
  double sumOfMeanDifferences=sumOfMeanDifferences(x,y);
  double xDifferenceOfMean=sumOfMeanDifferencesOnePoint(x);
  double w_1=sumOfMeanDifferences/xDifferenceOfMean;
  double w_0=meanY  - (w_1) * meanX;
  //double w_1=(n*sumOfProducts(x,y) - sum(x) * sum(y))/(n*sumOfSquares(x) - Math.pow(sum(x),2));
  //	double w_0=(sum(y) - (w_1 * sum(x)))/n;
  double[] ret = new double[vector.size()];
  ret[0]=w_0;
  ret[1]=w_1;
  return ret;
}//end weightsFor