List of variance() Examples

Examples of variance()

flanagan.analysis.Stat.variance()
net.jcores.jre.cores.CoreNumber.variance()
Returns the variance of all enclosed numbers, assuming a uniform distribution.

Examples:
- $(2, -2, 2, -2).variance() - Returns 4.0.
Single-threaded.
>
@since 1.0 @return The variance of all enclosed numbers. If no numbers are enclosed, 0 is returned.
org.jquantlib.math.statistics.GenericSequenceStatistics.variance()
org.jquantlib.processes.GeneralizedBlackScholesProcess.variance()
org.jquantlib.processes.StochasticProcess1D.variance()
Returns the variance {@latex$} V(x_t_0 + \Delta t} | x_{t_0} = x_0) } of the process after a time interval {@latex$ \Delta t }according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.
umontreal.iro.lecuyer.stat.Tally.variance()
Returns the sample variance of the observations since the last initialization. This returns Double.NaN if the tally contains less than two observations. @return the variance of the observations
weka.core.Instances.variance()
Computes the variance for a numeric attribute. @param attIndex the numeric attribute (index starts with 0) @return the variance if the attribute is numeric @throws IllegalArgumentException if the attribute is not numeric

Examples of weka.core.Instances.variance()

    m_FullMeansOrMediansOrModes = moveCentroid(0, instances, false);
    for (int i = 0; i < instances.numAttributes(); i++) {
      m_FullMissingCounts[i] = instances.attributeStats(i).missingCount;
      if (instances.attribute(i).isNumeric()) {
        if (m_displayStdDevs) {
          m_FullStdDevs[i] = Math.sqrt(instances.variance(i));
        }
        if (m_FullMissingCounts[i] == instances.numInstances()) {
          m_FullMeansOrMediansOrModes[i] = Double.NaN; // mark missing as mean
        }
      } else {

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Examples of weka.core.Instances.variance()

    // Check conversion is OK
    for (int j = 0; j < result.numAttributes(); j++) {
      if (result.attribute(j).isNumeric()) {
  double mean = result.meanOrMode(j);
  assertTrue("Mean should be 0", Utils.eq(mean, 0));
  double stdDev = Math.sqrt(result.variance(j));
  assertTrue("StdDev should be 1 (or 0)", 
       Utils.eq(stdDev, 0) || Utils.eq(stdDev, 1));
      }
    }
  }

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Examples of weka.core.Instances.variance()

      m_StdDevs = new double[input.numAttributes()];
      for (int i = 0; i < input.numAttributes(); i++) {
  if (input.attribute(i).isNumeric() &&
      (input.classIndex() != i)) {
    m_Means[i] = input.meanOrMode(i);
    m_StdDevs[i] = Math.sqrt(input.variance(i));
  }
      }


      // Convert pending input instances
      for(int i = 0; i < input.numInstances(); i++) {

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Examples of weka.core.Instances.variance()

    for (int i = 0; i < instances.numAttributes(); i++) {
      m_FullMissingCounts[i] = instances.attributeStats(i).missingCount;
      m_FullMeansOrModes[i] = instances.meanOrMode(i);
      if (instances.attribute(i).isNumeric()) {
        if (m_displayStdDevs) {
          m_FullStdDevs[i] = Math.sqrt(instances.variance(i));
        }
        if (m_FullMissingCounts[i] == instances.numInstances()) {
          m_FullMeansOrModes[i] = Double.NaN; // mark missing as mean
        }
      } else {

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Examples of weka.core.Instances.variance()

    for(int v=0; v < pnum; v++){
      //Instance px = pos.instance(v);
      Instances pxi =  pos.instance(v).relationalValue(1);
      for (int k=0; k<pxi.numAttributes(); k++) {
        m_MeanP[v][k] = pxi.meanOrMode(k);
        varP[v][k] = pxi.variance(k);
      }


      for (int w=0,t=0; w < m_Dimension; w++,t++){    
        //if((t==m_ClassIndex) || (t==m_IdIndex))
        //  t++;

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Examples of weka.core.Instances.variance()

    for(int v=0; v < nnum; v++){
      //Instance nx = neg.instance(v);
      Instances nxi = neg.instance(v).relationalValue(1);
      for (int k=0; k<nxi.numAttributes(); k++) {
        m_MeanN[v][k] = nxi.meanOrMode(k);
        varN[v][k] = nxi.variance(k);
      }
      //Instances nxi =  nx.getInstances();


      for (int w=0,t=0; w < m_Dimension; w++,t++){

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Examples of weka.core.Instances.variance()

        */


      Instances pxi =  pos.instance(v).relationalValue(1);
      for (int k=0; k<pxi.numAttributes(); k++) { 
        m_MeanP[v][k] = pxi.meanOrMode(k);
        m_VarianceP[v][k] = pxi.variance(k);
      }


      for (int w=0,t=0; w < m_Dimension; w++,t++){    
        //if((t==m_ClassIndex) || (t==m_IdIndex))
        //  t++;

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Examples of weka.core.Instances.variance()

        Instances nxi =  nx.getInstances();
        */
      Instances nxi =  neg.instance(v).relationalValue(1);
      for (int k=0; k<nxi.numAttributes(); k++) {
        m_MeanN[v][k] = nxi.meanOrMode(k);
        m_VarianceN[v][k] = nxi.variance(k);
      }


      for (int w=0,t=0; w < m_Dimension; w++,t++){    
        //if((t==m_ClassIndex) || (t==m_IdIndex))
        //  t++;

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Examples of weka.core.Instances.variance()

    double[] n = new double[m_Dimension];
    double [] xBar = new double[m_Dimension];
    double [] sSq = new double[m_Dimension];
    for (int i=0; i<exi.numAttributes() ; i++){
      xBar[i] = exi.meanOrMode(i);
      sSq[i] = exi.variance(i);
    }


    for (int w=0, t=0; w < m_Dimension; w++, t++){
      //if((t==m_ClassIndex) || (t==m_IdIndex))
      //t++;

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Examples of weka.core.Instances.variance()

      m_StdDevs = new double[input.numAttributes()];
      for (int i = 0; i < input.numAttributes(); i++) {
  if (input.attribute(i).isNumeric() &&
      (input.classIndex() != i)) {
    m_Means[i] = input.meanOrMode(i);
    m_StdDevs[i] = Math.sqrt(input.variance(i));
  }
      }


      // Convert pending input instances
      for(int i = 0; i < input.numInstances(); i++) {

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