/external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
H A D | AbstractDistribution.java | 17 package org.apache.commons.math.distribution; 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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H A D | ContinuousDistribution.java | 17 package org.apache.commons.math.distribution; 28 * 2.1, all continuous distribution implementations included in commons-math 36 * For this distribution, X, this method returns x such that P(X < x) = p.
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H A D | DiscreteDistribution.java | 17 package org.apache.commons.math.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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H A D | Distribution.java | 17 package org.apache.commons.math.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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H A D | 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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H A D | TDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | BetaDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | BinomialDistribution.java | 17 package org.apache.commons.math.distribution; 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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H A D | CauchyDistribution.java | 18 package org.apache.commons.math.distribution; 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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H A D | ChiSquaredDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | ExponentialDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | FDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | GammaDistribution.java | 17 package org.apache.commons.math.distribution;
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H A D | HypergeometricDistribution.java | 18 package org.apache.commons.math.distribution;
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H A D | 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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H A D | NormalDistribution.java | 18 package org.apache.commons.math.distribution; 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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H A D | 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 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. 66 * Change the probability of success for this distribution [all...] |
H A D | PoissonDistribution.java | 17 package org.apache.commons.math.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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H A D | WeibullDistribution.java | 18 package org.apache.commons.math.distribution; 22 * distribution as defined by
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H A D | ZipfDistribution.java | 18 package org.apache.commons.math.distribution; 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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H A D | 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/caliper/examples/src/main/java/examples/ |
H A D | ArraySortBenchmark.java | 33 @Param private Distribution distribution; field in class:ArraySortBenchmark 39 values = distribution.create(length);
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/external/tensorflow/tensorflow/compiler/xla/tests/ |
H A D | test_utils.h | 46 std::uniform_real_distribution<> distribution; local 48 (max_ - min_) * distribution(generator_));
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/external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
H A D | conditional_distribution.py | 15 """Conditional distribution base class.""" 21 from tensorflow.python.ops.distributions import distribution namespace 25 class ConditionalDistribution(distribution.Distribution): 28 Subclasses of this distribution may have additional keyword arguments passed
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H A D | estimator.py | 40 """Creates a `Head` for regression under a generic distribution. 134 d = self.distribution(logits) 150 d = self.distribution(logits) 168 def distribution(self, logits, name=None): member in class:_DistributionRegressionHead 169 """Retrieves a distribution instance, parameterized by `logits`. 173 underlying distribution. 175 Default value: "distribution". 178 distribution: `tf.Distribution` instance parameterized by `logits`. 180 with ops.name_scope(name, "distribution", [logits]):
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