How to use

org.apache.commons.math.stat.descriptive.moment.SecondMoment

constructor

/**
 * Constructs a Variance with default (true) <code>isBiasCorrected</code>
 * property.
 */
public Variance() {
  moment = new SecondMoment();
}

/**
 * Constructs a Variance with default (true) <code>isBiasCorrected</code>
 * property.
 */
public Variance() {
  moment = new SecondMoment();
}

/**
 * Constructs a Variance with the specified <code>isBiasCorrected</code>
 * property
 * 
 * @param isBiasCorrected  setting for bias correction - true means
 * bias will be corrected and is equivalent to using the argumentless
 * constructor
 */
public Variance(boolean isBiasCorrected) {
  moment = new SecondMoment();
  this.isBiasCorrected = isBiasCorrected;
}

/**
 * Constructs a Variance with the specified <code>isBiasCorrected</code>
 * property
 *
 * @param isBiasCorrected  setting for bias correction - true means
 * bias will be corrected and is equivalent to using the argumentless
 * constructor
 */
public Variance(boolean isBiasCorrected) {
  moment = new SecondMoment();
  this.isBiasCorrected = isBiasCorrected;
}

/**
 * Constructs a Variance with default (true) <code>isBiasCorrected</code>
 * property.
 */
public Variance() {
  moment = new SecondMoment();
}

/**
 * Constructs a Variance with the specified <code>isBiasCorrected</code>
 * property
 *
 * @param isBiasCorrected  setting for bias correction - true means
 * bias will be corrected and is equivalent to using the argumentless
 * constructor
 */
public Variance(boolean isBiasCorrected) {
  moment = new SecondMoment();
  this.isBiasCorrected = isBiasCorrected;
}

/**
 * {@inheritDoc}
 */
@Override
public SecondMoment copy() {
  SecondMoment result = new SecondMoment();
  copy(this, result);
  return result;
}

/**
 * {@inheritDoc}
 */
@Override
public SecondMoment copy() {
  SecondMoment result = new SecondMoment();
  copy(this, result);
  return result;
}

/**
 * <p>Returns the sum of squared deviations of Y from its mean.</p>
 *
 * <p>If the model has no intercept term, <code>0</code> is used for the
 * mean of Y - i.e., what is returned is the sum of the squared Y values.</p>
 *
 * <p>The value returned by this method is the SSTO value used in
 * the {@link #calculateRSquared() R-squared} computation.</p>
 *
 * @return SSTO - the total sum of squares
 * @see #isNoIntercept()
 * @since 2.2
 */
public double calculateTotalSumOfSquares() {
  if (isNoIntercept()) {
    return StatUtils.sumSq(Y.getData());
  } else {
    return new SecondMoment().evaluate(Y.getData());
  }
}

  geometricMean = descriptiveStats.getGeometricMean();
  sumOfSquares = descriptiveStats.getSumsq();
  secondMoment = new SecondMoment().evaluate(descriptiveStats.getValues());
} else {
  final SummaryStatistics summaryStats = (SummaryStatistics) s;

  geometricMean = descriptiveStats.getGeometricMean();
  sumOfSquares = descriptiveStats.getSumsq();
  secondMoment = new SecondMoment().evaluate(descriptiveStats.getValues());
} else {
  final SummaryStatistics summaryStats = (SummaryStatistics) s;