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/dports/devel/boost-python-libs/boost_1_72_0/libs/math/test/
H A Dbivariate_statistics_test.cpp36 using boost::math::statistics::covariance;
73 cov3 = covariance(u3, v3); in test_covariance()
76 cov3 = covariance(v3, u3); in test_covariance()
81 cov3 = covariance(u3, u3); in test_covariance()
109 Real cov_uu = covariance(u, u); in test_covariance()
111 Real cov_vv = covariance(v, v); in test_covariance()
/dports/devel/boost-docs/boost_1_72_0/libs/math/test/
H A Dbivariate_statistics_test.cpp36 using boost::math::statistics::covariance;
73 cov3 = covariance(u3, v3); in test_covariance()
76 cov3 = covariance(v3, u3); in test_covariance()
81 cov3 = covariance(u3, u3); in test_covariance()
109 Real cov_uu = covariance(u, u); in test_covariance()
111 Real cov_vv = covariance(v, v); in test_covariance()
/dports/math/R-cran-energy/energy/man/
H A Ddcovu.Rd1 \name{Unbiased distance covariance}
7 covariance and a bias-corrected estimator of
32 Unbiased distance covariance (SR2014) corresponds to the biased
35 For the original distance covariance test of independence (SRB2007,
36 SR2009), the distance covariance test statistic is the V-statistic
71 \concept{ distance covariance }
/dports/science/gnudatalanguage/gdl-1.0.1/src/pro/
H A Dcorrelate.pro12 function CORRELATE, x, y, covariance=covariance, double=double
30 if KEYWORD_SET(covariance) then return, cov
51 ;; cov[i, j] = CORRELATE(x[i, *], x[j, *], double=double, covariance=covariance)
66 if KEYWORD_SET(covariance) then return, cov / (dims[1]-1)
/dports/devel/boost-libs/boost_1_72_0/libs/math/test/
H A Dbivariate_statistics_test.cpp36 using boost::math::statistics::covariance;
73 cov3 = covariance(u3, v3); in test_covariance()
76 cov3 = covariance(v3, u3); in test_covariance()
81 cov3 = covariance(u3, u3); in test_covariance()
109 Real cov_uu = covariance(u, u); in test_covariance()
111 Real cov_vv = covariance(v, v); in test_covariance()
/dports/devel/hyperscan/boost_1_75_0/libs/math/test/
H A Dbivariate_statistics_test.cpp36 using boost::math::statistics::covariance;
73 cov3 = covariance(u3, v3); in test_covariance()
76 cov3 = covariance(v3, u3); in test_covariance()
81 cov3 = covariance(u3, u3); in test_covariance()
109 Real cov_uu = covariance(u, u); in test_covariance()
111 Real cov_vv = covariance(v, v); in test_covariance()
/dports/math/openturns/openturns-1.18/lib/src/Base/Algo/
H A DKarhunenLoeveAlgorithmImplementation.cxx45 …veAlgorithmImplementation::KarhunenLoeveAlgorithmImplementation(const CovarianceModel & covariance, in KarhunenLoeveAlgorithmImplementation() argument
48 , covariance_(covariance) in KarhunenLoeveAlgorithmImplementation()
93 void KarhunenLoeveAlgorithmImplementation::setCovarianceModel(const CovarianceModel & covariance) in setCovarianceModel() argument
95 covariance_ = covariance; in setCovarianceModel()
/dports/science/R-cran-etm/etm/man/
H A Dprint.etm.Rd8 \S3method{print}{etm}(x, covariance = FALSE, whole = TRUE, ...)
12 \item{covariance}{Whether print the covariance matrix. Default is
14 \item{whole}{Whether to plot the entire covariance matrix. If set to
/dports/math/openturns/openturns-1.18/python/test/
H A Dt_Dirac_std.expout7 covariance= 0.0
25 covariance= [[ 0 ]]
40 covariance= [[ 0 0 0 0 ]
58 covariance= [[ 0 0 0 0 ]
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/nonparametric/
H A Dkdecovclass.py18 def __init__(self, dataset, covariance): argument
19 self.covariance = covariance
23 self.inv_cov = np.linalg.inv(self.covariance)
24 self._norm_factor = np.sqrt(np.linalg.det(2*np.pi*self.covariance)) * self.n
34 self.inv_cov = np.linalg.inv(self.covariance)
35 self._norm_factor = np.sqrt(np.linalg.det(2*np.pi*self.covariance)) * self.n
/dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/covariance/
H A D_shrunk_covariance.py178 covariance = empirical_covariance(X, assume_centered=self.assume_centered)
179 covariance = shrunk_covariance(covariance, self.shrinkage)
180 self._set_covariance(covariance)
478 covariance, shrinkage = ledoit_wolf(
482 self._set_covariance(covariance)
680 covariance, shrinkage = oas(X - self.location_, assume_centered=True)
682 self._set_covariance(covariance)
/dports/science/py-nilearn/nilearn-0.8.1/nilearn/_utils/
H A Dglm.py243 def multiple_mahalanobis(effect, covariance): argument
263 if covariance.ndim == 2:
264 covariance = covariance[:, :, np.newaxis]
265 if effect.shape[0] != covariance.shape[0]:
267 if covariance.shape[0] != covariance.shape[1]:
271 Xt, Kt = np.ascontiguousarray(effect.T), np.ascontiguousarray(covariance.T)
/dports/science/dakota/dakota-6.13.0-release-public.src-UI/docs/KeywordMetadata/
H A DDUPLICATE-full_covariance2 Display the full covariance matrix
4 With a large number of responses, the covariance matrix can
6 force Dakota to output the full covariance matrix.
H A DDUPLICATE-diagonal_covariance2 Display only the diagonal terms of the covariance matrix
4 With a large number of responses, the covariance matrix can
6 suppress the off-diagonal covariance terms (to save compute and
/dports/math/R-cran-robustbase/robustbase/tests/
H A DMCD-specials.Rout.save90 alpha = 1: The minimum covariance determinant estimates based on 52 observations
134 alpha = 1: The minimum covariance determinant estimates based on 52 observations
226 alpha = 1: The minimum covariance determinant estimates based on 12 observations
230 The classical covariance matrix is singular.
273 alpha = 1: The minimum covariance determinant estimates based on 12 observations
277 The classical covariance matrix is singular.
312 The covariance matrix of the data is singular.
328 In covMcd(X) : The covariance matrix of the data is singular.
338 The covariance matrix of the data is singular.
365 The classical covariance matrix is singular.
[all …]
/dports/emulators/mess/mame-mame0226/3rdparty/bimg/3rdparty/nvtt/nvmath/
H A Dfitting.h19 Vector3 computeCovariance(int n, const Vector3 * points, float * covariance);
20 …(int n, const Vector3 * points, const float * weights, const Vector3 & metric, float * covariance);
22 Vector4 computeCovariance(int n, const Vector4 * points, float * covariance);
23 …(int n, const Vector4 * points, const float * weights, const Vector4 & metric, float * covariance);
/dports/emulators/mame/mame-mame0226/3rdparty/bimg/3rdparty/nvtt/nvmath/
H A Dfitting.h19 Vector3 computeCovariance(int n, const Vector3 * points, float * covariance);
20 …(int n, const Vector3 * points, const float * weights, const Vector3 & metric, float * covariance);
22 Vector4 computeCovariance(int n, const Vector4 * points, float * covariance);
23 …(int n, const Vector4 * points, const float * weights, const Vector4 & metric, float * covariance);
/dports/finance/R-cran-gmm/gmm/man/
H A Dvcov.Rd6 \title{Variance-covariance matrix of GMM or GEL}
20 \item{lambda}{If set to TRUE, the covariance matrix of the Lagrange multipliers is produced.}
21 \item{type}{Type of covariance matrix for the meat}
24 misspecification covariance matrix}
29 For tsls(), if vcov is set to a different value thand "Classical", a sandwich covariance matrix is …
/dports/www/qt5-webengine/qtwebengine-everywhere-src-5.15.2/src/3rdparty/chromium/third_party/webrtc/modules/audio_processing/ns/
H A Dsignal_model_estimator.cc41 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()
/dports/net-im/tg_owt/tg_owt-d578c76/src/modules/audio_processing/ns/
H A Dsignal_model_estimator.cc41 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()
/dports/www/chromium-legacy/chromium-88.0.4324.182/third_party/webrtc/modules/audio_processing/ns/
H A Dsignal_model_estimator.cc41 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()
/dports/www/firefox/firefox-99.0/third_party/libwebrtc/modules/audio_processing/ns/
H A Dsignal_model_estimator.cc41 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()
/dports/audio/webrtc-audio-processing/webrtc-audio-processing-1.0/webrtc/modules/audio_processing/ns/
H A Dsignal_model_estimator.cc41 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()
/dports/math/cgal/CGAL-5.3/include/CGAL/Scale_space_reconstruction_3/
H A DWeighted_PCA_smoother.h304 std::array<FT, 6> covariance = {{ 0., 0., 0., 0., 0., 0. }}; in operator() local
314 covariance[0] += w * v.x () * v.x (); in operator()
315 covariance[1] += w * v.x () * v.y (); in operator()
316 covariance[2] += w * v.x () * v.z (); in operator()
317 covariance[3] += w * v.y () * v.y (); in operator()
318 covariance[4] += w * v.y () * v.z (); in operator()
319 covariance[5] += w * v.z () * v.z (); in operator()
328 (covariance, eigenvalues, eigenvectors); in operator()
/dports/math/openturns/openturns-1.18/python/src/
H A DAbsoluteExponential_doc.i.in2 "Absolute exponential covariance function.
28 The *absolute exponential* function is a stationary covariance function with dimension :math:`d=1`.
51 Create a standard absolute exponential covariance function:
63 Create an absolute exponential covariance function specifying only the scale vector (amplitude is f…
68 Create an absolute exponential covariance function specifying the scale vector and the amplitude :

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