| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_Igammac.pbtxt | 3 summary: "Compute the upper regularized incomplete Gamma function `Q(a, x)`."
5 The upper regularized incomplete Gamma function is defined as:
7 \\(Q(a, x) = Gamma(a, x) / Gamma(a) = 1 - P(a, x)\\)
11 \\(Gamma(a, x) = int_{x}^{\infty} t^{a-1} exp(-t) dt\\)
16 Gamma function.
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| D | api_def_Igamma.pbtxt | 3 summary: "Compute the lower regularized incomplete Gamma function `P(a, x)`."
5 The lower regularized incomplete Gamma function is defined as:
8 \\(P(a, x) = gamma(a, x) / Gamma(a) = 1 - Q(a, x)\\)
14 is the lower incomplete Gamma function.
17 Gamma function.
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| D | api_def_Lgamma.pbtxt | 3 summary: "Computes the log of the absolute value of `Gamma(x)` element-wise."
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| D | api_def_RandomGammaGrad.pbtxt | 4 summary: "Computes the derivative of a Gamma random sample w.r.t. `alpha`."
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| D | api_def_Digamma.pbtxt | 5 `Gamma(x)`), element-wise.
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| D | api_def_RandomGamma.pbtxt | 39 summary: "Outputs random values from the Gamma distribution(s) described by alpha."
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | gamma_test.py | 55 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta)
69 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta)
84 gamma = gamma_lib.Gamma(concentration=1., rate=rate)
95 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta)
115 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta)
137 gamma = gamma_lib.Gamma(concentration=alpha, rate=beta)
148 gamma = gamma_lib.Gamma(concentration=alpha_v, rate=beta_v)
158 gamma = gamma_lib.Gamma(concentration=alpha_v, rate=beta_v)
167 gamma = gamma_lib.Gamma(
176 gamma = gamma_lib.Gamma(
[all …]
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| D | BetaDistributionImpl.java | 22 import org.apache.commons.math.special.Gamma;
121 z = Gamma.logGamma(alpha) + Gamma.logGamma(beta) - Gamma.logGamma(alpha + beta); in recomputeZ()
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| D | TDistributionImpl.java | 25 import org.apache.commons.math.special.Gamma;
118 …return FastMath.exp(Gamma.logGamma(nPlus1Over2) - 0.5 * (FastMath.log(FastMath.PI) + FastMath.log(… in density()
119 Gamma.logGamma(n/2) - nPlus1Over2 * FastMath.log(1 + x * x /n)); in density()
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| D | GammaDistributionImpl.java | 24 import org.apache.commons.math.special.Gamma;
100 ret = Gamma.regularizedGammaP(alpha, x / beta); in cumulativeProbability()
206 …th.pow(x / beta, alpha - 1) / beta * FastMath.exp(-x / beta) / FastMath.exp(Gamma.logGamma(alpha)); in density()
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| D | WeibullDistributionImpl.java | 24 import org.apache.commons.math.special.Gamma;
316 return sc * FastMath.exp(Gamma.logGamma(1 + (1 / sh))); in calculateNumericalMean()
335 FastMath.exp(Gamma.logGamma(1 + (2 / sh))) - in calculateNumericalVariance()
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| D | SaddlePointExpansion.java | 19 import org.apache.commons.math.special.Gamma;
114 ret = Gamma.logGamma(z + 1.0) - (z + 0.5) * FastMath.log(z) + in getStirlingError()
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| D | PoissonDistributionImpl.java | 24 import org.apache.commons.math.special.Gamma;
219 return Gamma.regularizedGammaQ((double) x + 1, mean, epsilon, maxIterations); in cumulativeProbability()
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | gamma.py | 47 class Gamma(distribution.Distribution): class
173 super(Gamma, self).__init__(
288 class GammaWithSoftplusConcentrationRate(Gamma):
314 @kullback_leibler.RegisterKL(Gamma, Gamma)
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| D | distributions.py | 32 from tensorflow.python.ops.distributions.gamma import Gamma
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| D | exponential.py | 41 class Exponential(gamma.Gamma):
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/special/ |
| D | Beta.java | 196 ret = Gamma.logGamma(a) + Gamma.logGamma(b) - in logBeta()
197 Gamma.logGamma(a + b); in logBeta()
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| D | Erf.java | 58 double ret = Gamma.regularizedGammaP(0.5, x * x, 1.0e-15, 10000); in erf()
88 final double ret = Gamma.regularizedGammaQ(0.5, x * x, 1.0e-15, 10000); in erfc()
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| D | Gamma.java | 30 public class Gamma { class
74 private Gamma() { in Gamma() method in Gamma
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| /external/pdfium/third_party/lcms/ |
| D | 0026-more-unsupported-characters.patch | 65 - // Y = (Max <96> Min) * (X ^ Gamma) + Min
66 + // Y = (Max - Min) * (X ^ Gamma) + Min
69 - // a = (Max <96> Min) ^ ( 1 / Gamma)
70 + // a = (Max - Min) ^ ( 1 / Gamma)
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.distributions.-gamma.pbtxt | 1 path: "tensorflow.distributions.Gamma"
3 is_instance: "<class \'tensorflow.python.ops.distributions.gamma.Gamma\'>"
49 …w_nan_stats\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'True\', \'Gamma\'], "
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| D | tensorflow.distributions.pbtxt | 36 name: "Gamma"
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| /external/clang/test/Sema/ |
| D | exprs.c | 80 void test7(int *P, _Complex float Gamma) { in test7() argument
81 …P = (P-42) + Gamma*4; // expected-error {{invalid operands to binary expression ('int *' and '_Co… in test7()
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | chi2.py | 37 class Chi2(gamma.Gamma):
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| D | invert_test.py | 79 distribution=gamma_lib.Gamma(concentration=1., rate=2.),
|