| /external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
| D | CorrelatedRandomVectorGenerator.java | 98 RealMatrix covariance, double small, in CorrelatedRandomVectorGenerator() argument
102 int order = covariance.getRowDimension(); in CorrelatedRandomVectorGenerator()
108 decompose(covariance, small); in CorrelatedRandomVectorGenerator()
126 public CorrelatedRandomVectorGenerator(RealMatrix covariance, double small, in CorrelatedRandomVectorGenerator() argument
130 int order = covariance.getRowDimension(); in CorrelatedRandomVectorGenerator()
136 decompose(covariance, small); in CorrelatedRandomVectorGenerator()
188 private void decompose(RealMatrix covariance, double small) in decompose() argument
191 int order = covariance.getRowDimension(); in decompose()
192 double[][] c = covariance.getData(); in decompose()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| D | AbstractMultipleLinearRegression.java | 231 protected void validateCovarianceData(double[][] x, double[][] covariance) { in validateCovarianceData() argument
232 if (x.length != covariance.length) { in validateCovarianceData()
234 LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, x.length, covariance.length); in validateCovarianceData()
236 if (covariance.length > 0 && covariance.length != covariance[0].length) { in validateCovarianceData()
239 covariance.length, covariance[0].length); in validateCovarianceData()
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| D | GLSMultipleLinearRegression.java | 56 public void newSampleData(double[] y, double[][] x, double[][] covariance) { in newSampleData() argument
60 validateCovarianceData(x, covariance); in newSampleData()
61 newCovarianceData(covariance); in newSampleData()
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| /external/fonttools/Lib/fontTools/pens/ |
| D | statisticsPen.py | 36 self.covariance = 0
60 self.covariance = covariance = self.momentXY / area - meanX*meanY
67 correlation = covariance / (stddevX * stddevY)
70 slant = covariance / varianceY if varianceY != 0 else float("NaN")
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | dirichlet_multinomial_test.py | 258 dist.covariance(),
296 covariance = dist.covariance()
299 self.assertEqual([2, 2], covariance.get_shape())
300 self.assertAllClose(expected_covariance, self.evaluate(covariance))
333 covariance = dist.covariance()
337 self.assertEqual([4, 3, 3], covariance.get_shape())
338 self.assertAllClose(expected_covariance, self.evaluate(covariance))
351 covariance = dist.covariance()
352 covariance2 = dist2.covariance()
353 self.assertEqual([3, 5, 4, 4], covariance.get_shape())
[all …]
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| D | multinomial_test.py | 223 self.assertEqual((3, 3), dist.covariance().get_shape())
224 self.assertAllClose(expected_covariances, dist.covariance())
238 self.assertEqual((4, 2, 2, 2), dist.covariance().get_shape())
239 self.assertAllClose(expected_covariances, dist.covariance())
254 covariance = dist.covariance()
255 covariance2 = dist2.covariance()
256 self.assertEqual((3, 5, 4, 4), covariance.get_shape())
293 dist.covariance(),
324 dist.covariance(),
353 dist.covariance(),
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| /external/webrtc/modules/audio_processing/ns/ |
| D | signal_model_estimator.cc | 41 float covariance = 0.f; in ComputeSpectralDiff() local
47 covariance += signal_diff * noise_diff; in ComputeSpectralDiff()
51 covariance *= kOneByFftSizeBy2Plus1; in ComputeSpectralDiff()
57 signal_variance - (covariance * covariance) / (noise_variance + 0.0001f); in ComputeSpectralDiff()
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/correlation/ |
| D | Covariance.java | 166 double cov = covariance(matrix.getColumn(i), matrix.getColumn(j), biasCorrected); in computeCovarianceMatrix()
220 public double covariance(final double[] xArray, final double[] yArray, boolean biasCorrected) in covariance() method in Covariance
255 public double covariance(final double[] xArray, final double[] yArray) in covariance() method in Covariance
257 return covariance(xArray, yArray, true); in covariance()
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| D | PearsonsCorrelation.java | 95 public PearsonsCorrelation(Covariance covariance) { in PearsonsCorrelation() argument
96 RealMatrix covarianceMatrix = covariance.getCovarianceMatrix(); in PearsonsCorrelation()
100 nObs = covariance.getN(); in PearsonsCorrelation()
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| /external/ImageMagick/coders/ |
| D | dds.c | 2800 static void ComputePrincipleComponent(const float *covariance, in ComputePrincipleComponent() argument
2812 row0.x = covariance[0]; in ComputePrincipleComponent()
2813 row0.y = covariance[1]; in ComputePrincipleComponent()
2814 row0.z = covariance[2]; in ComputePrincipleComponent()
2817 row1.x = covariance[1]; in ComputePrincipleComponent()
2818 row1.y = covariance[3]; in ComputePrincipleComponent()
2819 row1.z = covariance[4]; in ComputePrincipleComponent()
2822 row2.x = covariance[2]; in ComputePrincipleComponent()
2823 row2.y = covariance[4]; in ComputePrincipleComponent()
2824 row2.z = covariance[5]; in ComputePrincipleComponent()
[all …]
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| /external/webrtc/modules/audio_processing/echo_detector/ |
| D | normalized_covariance_estimator.h | 31 float covariance() const { return covariance_; } in covariance() function
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.distributions.-distribution.pbtxt | 55 name: "covariance"
56 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-student-t.pbtxt | 68 name: "covariance"
69 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-exponential.pbtxt | 65 name: "covariance"
66 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-normal.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-laplace.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-uniform.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-gamma.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-bernoulli.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-beta.pbtxt | 68 name: "covariance"
69 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-multinomial.pbtxt | 68 name: "covariance"
69 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-dirichlet.pbtxt | 64 name: "covariance"
65 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-dirichlet-multinomial.pbtxt | 68 name: "covariance"
69 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| D | tensorflow.distributions.-categorical.pbtxt | 68 name: "covariance"
69 argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'covariance\'], "
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| /external/eigen/doc/ |
| D | DenseDecompositionBenchmark.dox | 12 …rices, the reported timmings include the cost to compute the symmetric covariance matrix \f$ A^T A…
30 …oblems, and the reported timing include the cost to form the symmetric covariance matrix \f$ A^T A…
34 …t of Cholesky/LU decompositions is dominated by the computation of the symmetric covariance matrix.
|