List of inverseCumulativeProbability() Examples

Examples of inverseCumulativeProbability()

org.apache.commons.math.distribution.ChiSquaredDistribution.inverseCumulativeProbability()
org.apache.commons.math.distribution.ChiSquaredDistributionImpl.inverseCumulativeProbability()
For this distribution, X, this method returns the critical point x, such that P(X < x) = p.
Returns 0 for p=0 and Double.POSITIVE_INFINITY for p=1.
@param p the desired probability @return x, such that P(X < x) = p @throws MathException if the inverse cumulative probability can not becomputed due to convergence or other numerical errors. @throws IllegalArgumentException if p is not a validprobability.
org.apache.commons.math.distribution.IntegerDistribution.inverseCumulativeProbability()
For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p.
Note that this definition implies:
- If there is a minimum value, m, with positive probability under (the density of) X, then m - 1 is returned by inverseCumulativeProbability(0). If there is no such value m, Integer.MIN_VALUE is returned.
- If there is a maximum value, M, such that P(X ≤ M) =1, then M is returned by inverseCumulativeProbability(1). If there is no such value, M, Integer.MAX_VALUE is returned.
@param p the cumulative probability. @return the largest x such that P(X ≤ x) <= p @throws MathException if the inverse cumulative probability can not becomputed due to convergence or other numerical errors. @throws IllegalArgumentException if p is not between 0 and 1 (inclusive)
org.apache.commons.math.distribution.NormalDistributionImpl.inverseCumulativeProbability()
For this distribution, X, this method returns the critical point x, such that P(X < x) = p.
Returns Double.NEGATIVE_INFINITY for p=0 and Double.POSITIVE_INFINITY for p=1.
@param p the desired probability @return x, such that P(X < x) = p @throws MathException if the inverse cumulative probability can not becomputed due to convergence or other numerical errors. @throws IllegalArgumentException if p is not a validprobability.
org.apache.commons.math.distribution.PoissonDistribution.inverseCumulativeProbability()
org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()
org.apache.commons.math.distribution.TDistribution.inverseCumulativeProbability()
org.apache.commons.math.distribution.TDistributionImpl.inverseCumulativeProbability()
For this distribution, X, this method returns the critical point x, such that P(X < x) = p.
Returns Double.NEGATIVE_INFINITY for p=0 and Double.POSITIVE_INFINITY for p=1.
@param p the desired probability @return x, such that P(X < x) = p @throws MathException if the inverse cumulative probability can not becomputed due to convergence or other numerical errors. @throws IllegalArgumentException if p is not a validprobability.
org.apache.commons.math.distribution.ZipfDistributionImpl.inverseCumulativeProbability()
org.apache.commons.math3.distribution.BinomialDistribution.inverseCumulativeProbability()
{@inheritDoc}Returns {@code 0} when {@code p= = 0} and{@code Double.POSITIVE_INFINITY} when {@code p == 1}.
org.apache.commons.math3.distribution.ExponentialDistribution.inverseCumulativeProbability()
{@inheritDoc}Returns {@code 0} when {@code p= = 0} and{@code Double.POSITIVE_INFINITY} when {@code p == 1}.
org.apache.commons.math3.distribution.FDistribution.inverseCumulativeProbability()
{@inheritDoc}Returns {@code 0} when {@code p= = 0} and{@code Double.POSITIVE_INFINITY} when {@code p == 1}.
org.apache.commons.math3.distribution.NormalDistribution.inverseCumulativeProbability()
{@inheritDoc} @since 3.2
org.apache.commons.math3.distribution.RealDistribution.inverseCumulativeProbability()
Computes the quantile function of this distribution. For a random variable {@code X} distributed according to this distribution, thereturned value is
- inf{x in R | P(X<=x)>= p} for {@code 0 < p <= 1},
- inf{x in R | P(X<=x)> 0} for {@code p = 0}.
@param p the cumulative probability @return the smallest {@code p}-quantile of this distribution (largest 0-quantile for {@code p = 0}) @throws OutOfRangeException if {@code p < 0} or {@code p> 1}
org.apache.commons.math3.distribution.TDistribution.inverseCumulativeProbability()
{@inheritDoc}Returns {@code 0} when {@code p= = 0} and{@code Double.POSITIVE_INFINITY} when {@code p == 1}.
org.apache.commons.math3.distribution.WeibullDistribution.inverseCumulativeProbability()
{@inheritDoc}Returns {@code 0} when {@code p == 0} and{@code Double.POSITIVE_INFINITY} when {@code p == 1}.

Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private RandomAccessSparseVector generateRandomDoc(int numWords, double sparsity) throws MathException {
    RandomAccessSparseVector v = new RandomAccessSparseVector(numWords,(int)(numWords * sparsity));
    PoissonDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.set(i,dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }


  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private Vector generateRandomDoc(int numWords, double sparsity) throws MathException {
    Vector v = new DenseVector(numWords);
    IntegerDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.setQuick(i, dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }
  
  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private RandomAccessSparseVector generateRandomDoc(int numWords, double sparsity) throws MathException {
    RandomAccessSparseVector v = new RandomAccessSparseVector(numWords,(int)(numWords * sparsity));
    IntegerDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.set(i,dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }


  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private RandomAccessSparseVector generateRandomDoc(int numWords, double sparsity) throws MathException {
    RandomAccessSparseVector v = new RandomAccessSparseVector(numWords,(int)(numWords * sparsity));
    IntegerDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.set(i,dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }


  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private SparseVector generateRandomDoc(int numWords, double sparsity) throws MathException {
    SparseVector v = new SparseVector(numWords,(int)(numWords * sparsity));
    PoissonDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.set(i,dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }


  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.PoissonDistributionImpl.inverseCumulativeProbability()

  private Vector generateRandomDoc(int numWords, double sparsity) throws MathException {
    Vector v = new DenseVector(numWords);
    PoissonDistribution dist = new PoissonDistributionImpl(sparsity);
    for (int i = 0; i < numWords; i++) {
      // random integer
      v.setQuick(i, dist.inverseCumulativeProbability(random.nextDouble()) + 1);
    }
    return v;
  }


  private LDAState generateRandomState(int numWords, int numTopics) {

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Examples of org.apache.commons.math.distribution.TDistribution.inverseCumulativeProbability()

  public static Object statTinv(Object[] args, XelContext ctx) throws MathException{
    double p = CommonFns.toNumber(args[0]).doubleValue();
    double degree_freedom = CommonFns.toNumber(args[1]).doubleValue();
    DistributionFactory factory = DistributionFactory.newInstance();
    TDistribution td = factory.createTDistribution(degree_freedom );
    return UtilFns.validateNumber(td.inverseCumulativeProbability((1-p)));
  }
  
  /**
   * Returns the weibull distribution
   * @param args arguments

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Examples of org.apache.commons.math.distribution.TDistributionImpl.inverseCumulativeProbability()

  public static Double tDistInverseCDF(double p_value, int dof)
  {
    TDistributionImpl tdist = new TDistributionImpl(dof);
    try
    {
      return tdist.inverseCumulativeProbability(p_value);
    }
    catch (MathException e)
    {
      e.printStackTrace();
    }

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Examples of org.apache.commons.math.distribution.ZipfDistributionImpl.inverseCumulativeProbability()


    int numAccts = (Integer) state.get("numAccts");
    // note: non integer exponents are slow


    ZipfDistributionImpl zdiBanks = new ZipfDistributionImpl((Integer) state.get("numBanks"), 1);
    String bank = Utils.getBank(zdiBanks.inverseCumulativeProbability(rand.nextDouble()));
    ZipfDistributionImpl zdiAccts = new ZipfDistributionImpl(numAccts, 1);
    String acct1 = Utils.getAccount(zdiAccts.inverseCumulativeProbability(rand.nextDouble()));
    String acct2 = Utils.getAccount(zdiAccts.inverseCumulativeProbability(rand.nextDouble()));
    while (acct2.equals(acct1)) {
      // intentionally not using zipf distribution to pick on retry

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Examples of org.apache.commons.math3.distribution.BinomialDistribution.inverseCumulativeProbability()

                inRange++;
            }
        }


        BinomialDistribution binomial = new BinomialDistribution(numberOfRuns, getConfidence());
        int lowerBound = binomial.inverseCumulativeProbability(0.01);
        int upperBound = binomial.inverseCumulativeProbability(0.99);
        assertTrue(lowerBound < inRange && inRange < upperBound, String.format("%d out of %d passed. Expected [%d, %d]", inRange, numberOfRuns, lowerBound, upperBound));
    }


    @Override

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