| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| ContinuousDistribution.java | 17 package org.apache.commons.math.distribution;
28 * 2.1, all continuous distribution implementations included in commons-math
33 public interface ContinuousDistribution extends Distribution {
36 * For this distribution, X, this method returns x such that P(X < x) = p.
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| DiscreteDistribution.java | 17 package org.apache.commons.math.distribution;
25 public interface DiscreteDistribution extends Distribution {
28 * to this distribution, this method returns P(X = x). In other words, this
29 * method represents the probability mass function, or PMF for the distribution.
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| Distribution.java | 17 package org.apache.commons.math.distribution;
26 public interface Distribution {
29 * to this distribution, this method returns P(X ≤ x). In other words,
30 * this method represents the (cumulative) distribution function, or
31 * CDF, for this distribution.
33 * @param x the value at which the distribution function is evaluated.
35 * distribution takes a value less than or equal to <code>x</code>
43 * to this distribution, this method returns P(x0 ≤ X ≤ x1).
47 * @return the probability that a random variable with this distribution
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| HasDensity.java | 18 package org.apache.commons.math.distribution;
23 * <p>Interface that signals that a distribution can compute the probability density function
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| BinomialDistribution.java | 17 package org.apache.commons.math.distribution;
20 * The Binomial Distribution.
26 * Binomial Distribution</a></li>
34 * Access the number of trials for this distribution.
40 * Access the probability of success for this distribution.
46 * Change the number of trials for this distribution.
54 * Change the probability of success for this distribution.
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| CauchyDistribution.java | 18 package org.apache.commons.math.distribution;
21 * Cauchy Distribution.
27 * Cauchy Distribution</a></li>
38 * @return median for this distribution
44 * @return scale parameter for this distribution
50 * @param median for this distribution
58 * @param s scale parameter for this distribution
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| ChiSquaredDistribution.java | 17 package org.apache.commons.math.distribution;
20 * The Chi-Squared Distribution.
26 * Chi-Squared Distribution</a></li>
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| ExponentialDistribution.java | 17 package org.apache.commons.math.distribution;
20 * The Exponential Distribution.
26 * Exponential Distribution</a></li>
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| FDistribution.java | 17 package org.apache.commons.math.distribution;
20 * F-Distribution.
25 * <li><a href="http://mathworld.wolfram.com/F-Distribution.html">
26 * F-Distribution</a></li>
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| IntegerDistribution.java | 17 package org.apache.commons.math.distribution;
29 * to this distribution, this method returns P(X = x). In other words, this
30 * method represents the probability mass function for the distribution.
39 * to this distribution, this method returns P(X ≤ x). In other words,
40 * this method represents the probability distribution function, or PDF
41 * for the distribution.
44 * @return PDF for this distribution.
51 * For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
62 * For this distribution, X, this method returns the largest x such that
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| PascalDistribution.java | 17 package org.apache.commons.math.distribution;
20 * The Pascal distribution. The Pascal distribution is a special case of the
21 * Negative Binomial distribution where the number of successes parameter is an
24 * There are various ways to express the probability mass and distribution
25 * functions for the Pascal distribution. The convention employed by the
33 * Negative Binomial Distribution</a></li>
43 * Access the number of successes for this distribution.
50 * Access the probability of success for this distribution.
57 * Change the number of successes for this distribution
[all...] |
| PoissonDistribution.java | 17 package org.apache.commons.math.distribution;
22 * Interface representing the Poisson Distribution.
28 * Poisson distribution</a></li>
37 * Get the mean for the distribution.
39 * @return the mean for the distribution.
44 * Set the mean for the distribution.
56 * Calculates the Poisson distribution function using a normal approximation.
59 * @return the distribution function value calculated using a normal approximation
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| TDistribution.java | 17 package org.apache.commons.math.distribution;
20 * Student's t-Distribution.
25 * <li><a href="http://mathworld.wolfram.com/Studentst-Distribution.html">
26 * Student's t-Distribution</a></li>
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| WeibullDistribution.java | 18 package org.apache.commons.math.distribution;
21 * Weibull Distribution. This interface defines the two parameter form of the
22 * distribution as defined by
24 * Weibull Distribution</a>, equations (1) and (2).
30 * Weibull Distribution</a></li>
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| ZipfDistribution.java | 18 package org.apache.commons.math.distribution;
21 * The Zipf (or zeta) Distribution.
26 * Distribution</a></li>
35 * Get the number of elements (e.g. corpus size) for the distribution.
42 * Set the number of elements (e.g. corpus size) for the distribution.
54 * Get the exponent characterising the distribution.
61 * Set the exponent characterising the distribution.
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| AbstractDistribution.java | 17 package org.apache.commons.math.distribution;
31 implements Distribution, Serializable {
45 * to this distribution, this method returns P(x0 ≤ X ≤ x1).
53 * @return the probability that a random variable with this distribution
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| BetaDistribution.java | 17 package org.apache.commons.math.distribution;
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| GammaDistribution.java | 17 package org.apache.commons.math.distribution;
20 * The Gamma Distribution.
26 * Gamma Distribution</a></li>
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| HypergeometricDistribution.java | 18 package org.apache.commons.math.distribution;
21 * The Hypergeometric Distribution.
27 * Hypergeometric Distribution</a></li>
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| NormalDistribution.java | 18 package org.apache.commons.math.distribution;
21 * Normal (Gauss) Distribution.
27 * Normal Distribution</a></li>
36 * @return mean for this distribution
41 * @param mean for this distribution
48 * @return standard deviation for this distribution
53 * @param sd standard deviation for this distribution
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| AbstractContinuousDistribution.java | 17 package org.apache.commons.math.distribution;
34 * provided for some of the methods that do not vary from distribution to
35 * distribution.
47 * RandomData instance used to generate samples from the distribution
78 * For this distribution, X, this method returns the critical point x, such
156 * Generates a random value sampled from this distribution. The default
169 * Generates a random sample from the distribution. The default implementation
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| ChiSquaredDistributionImpl.java | 17 package org.apache.commons.math.distribution;
41 /** Internal Gamma distribution. */
48 * Create a Chi-Squared distribution with the given degrees of freedom.
56 * Create a Chi-Squared distribution with the given degrees of freedom.
58 * @param g the underlying gamma distribution used to compute probabilities.
72 * Create a Chi-Squared distribution with the given degrees of freedom and
136 * For this distribution, X, this method returns P(X < x).
138 * @return CDF for this distribution.
147 * For this distribution, X, this method returns the critical point x, such
239 * Modify the underlying gamma distribution. The caller is responsible fo
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| SaddlePointExpansion.java | 17 package org.apache.commons.math.distribution;
169 * Compute the PMF for a binomial distribution using the saddle point
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/inference/ |
| ChiSquareTestImpl.java | 21 import org.apache.commons.math.distribution.ChiSquaredDistribution;
22 import org.apache.commons.math.distribution.ChiSquaredDistributionImpl;
34 /** Distribution used to compute inference statistics. */
35 private ChiSquaredDistribution distribution; field in class:ChiSquareTestImpl
45 * Create a test instance using the given distribution for computing
47 * @param x distribution used to compute inference statistics.
117 distribution.setDegreesOfFreedom(expected.length - 1.0);
118 return 1.0 - distribution.cumulativeProbability(
192 distribution.setDegreesOfFreedom(df);
193 return 1 - distribution.cumulativeProbability(chiSquare(counts))
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| /external/caliper/examples/src/main/java/examples/ |
| ArraySortBenchmark.java | 33 @Param private Distribution distribution; field in class:ArraySortBenchmark
39 values = distribution.create(length);
50 public enum Distribution {
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