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  /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/
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.
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>
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.
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
ChiSquaredDistribution.java 17 package org.apache.commons.math.distribution;
20 * The Chi-Squared Distribution.
26 * Chi-Squared Distribution</a></li>
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 &lt; x) = p.
Distribution.java 17 package org.apache.commons.math.distribution;
26 public interface Distribution {
29 * to this distribution, this method returns P(X &le; 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 &le; X &le; x1).
47 * @return the probability that a random variable with this distribution
ExponentialDistribution.java 17 package org.apache.commons.math.distribution;
20 * The Exponential Distribution.
26 * Exponential Distribution</a></li>
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>
GammaDistribution.java 17 package org.apache.commons.math.distribution;
20 * The Gamma Distribution.
26 * Gamma Distribution</a></li>
HasDensity.java 18 package org.apache.commons.math.distribution;
23 * <p>Interface that signals that a distribution can compute the probability density function
HypergeometricDistribution.java 18 package org.apache.commons.math.distribution;
21 * The Hypergeometric Distribution.
27 * Hypergeometric Distribution</a></li>
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
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
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>
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.
BetaDistribution.java 17 package org.apache.commons.math.distribution;
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 &le; 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 &le; X &le; x1).
62 * For this distribution, X, this method returns the largest x such that
  /packages/inputmethods/LatinIME/native/jni/tests/suggest/core/layout/
normal_distribution_2d_test.cpp 33 const NormalDistribution2D distribution(ORIGIN_X, LARGE_STANDARD_DEVIATION, ORIGIN_Y,
38 // The probability density of the point near the distribution center is larger than the
39 // probability density of the point that is far from distribution center.
40 EXPECT_GE(distribution.getProbabilityDensity(SMALL_COORDINATE, SMALL_COORDINATE),
41 distribution.getProbabilityDensity(LARGE_COORDINATE, LARGE_COORDINATE));
45 EXPECT_GE(distribution.getProbabilityDensity(LARGE_COORDINATE, SMALL_COORDINATE),
46 distribution.getProbabilityDensity(SMALL_COORDINATE, LARGE_COORDINATE));
52 const NormalDistribution2D distribution(ORIGIN_X, LARGE_STANDARD_DEVIATION, ORIGIN_Y,
58 // The probability density of the rotated distribution at the point and the probability
59 // density of the original distribution at the rotated point are the same
    [all...]
  /external/chromium-trace/catapult/third_party/gsutil/third_party/boto/boto/cloudfront/
object.py 28 self.distribution = bucket.distribution
31 return '<Object: %s/%s>' % (self.distribution.config.origin, self.name)
35 url += self.distribution.domain_name
  /packages/inputmethods/LatinIME/native/jni/tests/dictionary/utils/
bloom_filter_test.cpp 38 // Use the uniform integer distribution [0, TEST_RANDOM_DATA_MAX].
39 std::uniform_int_distribution<int> distribution(0, TEST_RANDOM_DATA_MAX);
40 auto randomNumberGenerator = std::bind(distribution, std::mt19937());
55 // Use the uniform integer distribution [0, 1].
56 std::uniform_int_distribution<int> distribution(0, 1);
57 auto randomBitGenerator = std::bind(distribution, std::mt19937());
  /external/libevent/include/event2/
event-config.h 11 # error No event-config.h suitable for this distribution.
  /external/libgdx/gdx/src/com/badlogic/gdx/graphics/g3d/particles/values/
WeightMeshSpawnShapeValue.java 14 private CumulativeDistribution<Triangle> distribution; field in class:WeightMeshSpawnShapeValue
18 distribution = new CumulativeDistribution<Triangle>();
24 distribution = new CumulativeDistribution<Triangle>();
36 distribution.clear();
57 distribution.add(new Triangle(x1, y1, z1, x2, y2, z2, x3, y3, z3), area);
70 distribution.add(new Triangle(x1, y1, z1, x2, y2, z2, x3, y3, z3), area);
74 //Generate cumulative distribution
75 distribution.generateNormalized();
80 Triangle t = distribution.value();
  /prebuilts/gdb/darwin-x86/lib/python2.7/distutils/command/
install_headers.py 36 headers = self.distribution.headers
46 return self.distribution.headers or []

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