How to use

SecondMoment

in

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

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

/**
 * {@inheritDoc}
 */
@Override
public void clear() {
  if (incMoment) {
    moment.clear();
  }
}

/**
 * {@inheritDoc}
 */
public long getN() {
  return moment.getN();
}

/**
 * {@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());
  }
}

/**
 * {@inheritDoc}
 */
@Override
public void increment(final double d) {
  if (n < 1) {
    m3 = m2 = m1 = 0.0;
  }
  double prevM2 = m2;
  super.increment(d);
  nDevSq = nDev * nDev;
  double n0 = n;
  m3 = m3 - 3.0 * nDev * prevM2 + (n0 - 1) * (n0 - 2) * nDevSq * dev;
}

/**
 * Copies source to dest.
 * <p>Neither source nor dest can be null.</p>
 *
 * @param source Variance to copy
 * @param dest Variance to copy to
 * @throws NullPointerException if either source or dest is null
 */
public static void copy(Variance source, Variance dest) {
  dest.moment = source.moment.copy();
  dest.isBiasCorrected = source.isBiasCorrected;
  dest.incMoment = source.incMoment;
}

/**
 * Returns a statistic related to the Second Central Moment.  Specifically,
 * what is returned is the sum of squared deviations from the sample mean
 * among the values that have been added.
 * <p>
 * Returns <code>Double.NaN</code> if no data values have been added and
 * returns <code>0</code> if there is just one value in the data set.</p>
 * <p>
 * @return second central moment statistic
 * @since 2.0
 */
public double getSecondMoment() {
  return secondMoment.getResult();
}

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

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

/**
 * {@inheritDoc}
 * <p>If all values are available, it is more accurate to use
 * {@link #evaluate(double[])} rather than adding values one at a time
 * using this method and then executing {@link #getResult}, since
 * <code>evaluate</code> leverages the fact that is has the full
 * list of values together to execute a two-pass algorithm.
 * See {@link Variance}.</p>
 */
@Override
public void increment(final double d) {
  if (incMoment) {
    moment.increment(d);
  }
}

/**
 * Copies source to dest.
 * <p>Neither source nor dest can be null.</p>
 *
 * @param source ThirdMoment to copy
 * @param dest ThirdMoment to copy to
 * @throws NullPointerException if either source or dest is null
 */
public static void copy(ThirdMoment source, ThirdMoment dest) {
  SecondMoment.copy(source, dest);
  dest.m3 = source.m3;
  dest.nDevSq = source.nDevSq;
}

/**
 * Returns a statistic related to the Second Central Moment.  Specifically,
 * what is returned is the sum of squared deviations from the sample mean
 * among the values that have been added.
 * <p>
 * Returns <code>Double.NaN</code> if no data values have been added and
 * returns <code>0</code> if there is just one value in the data set.</p>
 * <p>
 * @return second central moment statistic
 * @since 2.0
 */
public double getSecondMoment() {
  return secondMoment.getResult();
}

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

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

/**
 * {@inheritDoc}
 */
@Override
public void clear() {
  super.clear();
  m3 = Double.NaN;
  nDevSq = Double.NaN;
}

/**
 * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#increment(double)
 */
public void increment(final double d) {
  if (n < 1) {
    m3 = m2 = m1 = 0.0;
  }  
    double prevM2 = m2;
  super.increment(d);
  nDevSq = nDev * nDev;
  double n0 = (double) n;
  m3 = m3 - 3.0 * nDev * prevM2 + (n0 - 1) * (n0 - 2) * nDevSq * dev;
}

/**
 * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#getN()
 */
public long getN() {
  return moment.getN();
}

/**
 * Copies source to dest.
 * <p>Neither source nor dest can be null.</p>
 *
 * @param source ThirdMoment to copy
 * @param dest ThirdMoment to copy to
 * @throws NullPointerException if either source or dest is null
 */
public static void copy(ThirdMoment source, ThirdMoment dest) {
  SecondMoment.copy(source, dest);
  dest.m3 = source.m3;
  dest.nDevSq = source.nDevSq;
}

/**
 * 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;
}