/dports/science/dakota/dakota-6.13.0-release-public.src-UI/docs/KeywordMetadata/ |
H A D | method-bayes_calibration-queso | 30 There are a variety of ways the user can specify the proposal covariance matrix which 32 The proposal covariance specifies the covariance structure of a multivariate normal distribution. 37 the derived-based proposal covariance forms a more 39 …ions of the parameters being calibrated. When specifying the proposal covariance with values or f… 40 …oose to specify only the diagonals of the covariance matrix with \c diagonal or to specify the ful…
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H A D | model-random_field | 4 runs, or from a covariance matrix. The representation may then be sampled 9 runs, or from a covariance matrix. The random field may then be sampled 19 given a mesh and a covariance matrix governing how the field varies over the mesh. 22 covariance, the form of the covariance is defined with \c analytic_covariance. 27 of the covariance matrix of the field data. The only difference is in the treatment
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/dports/science/InsightToolkit/ITK-5.0.1/Testing/Data/Input/Statistics/ |
H A D | TwoDimensionTwoGaussian.Readme | 23 covariance 30 covariance 37 covariance 45 covariance
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/dports/multimedia/chilitags/chilitags-2.0.0-169-g0d9854f/src/ |
H A D | EstimatePose3D.cpp | 81 void EstimatePose3D<RealT>::setFilterProcessNoiseCovariance(cv::Mat const& covariance) in setFilterProcessNoiseCovariance() argument 83 mFilter3D.setProcessNoiseCovariance(covariance); in setFilterProcessNoiseCovariance() 87 void EstimatePose3D<RealT>::setFilterObservationNoiseCovariance(cv::Mat const& covariance) in setFilterObservationNoiseCovariance() argument 89 mFilter3D.setObservationNoiseCovariance(covariance); in setFilterObservationNoiseCovariance()
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/dports/math/R-cran-pls/pls/tests/RUnit/common/ |
H A D | runit.jackknife.R | 17 checkEquals(dim(var.jack(mod, covariance = TRUE)), 19 checkEquals(dim(var.jack(mod, ncomp = 1:2, covariance = TRUE)), 31 checkEquals(dim(var.jack(mod, covariance = TRUE)), 33 checkEquals(dim(var.jack(mod, ncomp = 1:2, covariance = TRUE)),
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/dports/science/gnudatalanguage/gdl-1.0.1/src/pro/ |
H A D | a_correlate.pro | 16 ; /covariance If set, then return the autocovariance instead. 30 function a_correlate, x, lag, covariance = covariance, double = double 52 if keyword_set(covariance) then rv /= nvals $
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/dports/math/scilab/scilab-6.1.1/scilab/modules/statistics/macros/ |
H A D | cov.sci | 15 // Sample covariance or cross covariance matrix 28 // C: a square matrix of doubles, the sample (cross)covariance 36 // cov(x, y) returns the 2-by-2 sample covariance matrix of x and 38 // an unbiased estimator of the covariance matrix 44 // cov(x) returns the nvar-by-nvar sample covariance matrix of X 45 // normalized by nobs-1, i.e. an unbiased estimator of the covariance 51 // cov(x) returns the nvar-by-mvar sample cross-covariance matrix of X 53 // cross-covariance matrix E[(X-E[X])(Y-E[Y])^T]
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/queso/src/stats/src/ |
H A D | GaussianLikelihoodDiagonalCovariance.C | 37 const V & observations, const V & covariance) in GaussianLikelihoodDiagonalCovariance() argument 39 m_covariance(covariance) in GaussianLikelihoodDiagonalCovariance() 41 if (covariance.sizeLocal() != observations.sizeLocal()) { in GaussianLikelihoodDiagonalCovariance()
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H A D | GaussianLikelihoodFullCovariance.C | 37 const V & observations, const M & covariance, double covarianceCoefficient) in GaussianLikelihoodFullCovariance() argument 40 m_covariance(covariance) in GaussianLikelihoodFullCovariance() 42 if (covariance.numRowsLocal() != observations.sizeLocal()) { in GaussianLikelihoodFullCovariance()
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/dports/math/cgal/CGAL-5.3/include/CGAL/ |
H A D | linear_least_squares_fitting_triangles_3.h | 53 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local 54 …assemble_covariance_matrix_3(first,beyond,covariance,c,k,(Triangle*) nullptr,tag, diagonalize_trai… in linear_least_squares_fitting_3() 57 return fitting_plane_3(covariance,c,plane,k,diagonalize_traits); in linear_least_squares_fitting_3() 142 typename DiagonalizeTraits::Covariance_matrix covariance = {{ 0., 0., 0., 0., 0., 0. }}; in linear_least_squares_fitting_3() local 143 …assemble_covariance_matrix_3(first,beyond,covariance,c,k,(Triangle*) nullptr,tag, diagonalize_trai… in linear_least_squares_fitting_3() 146 return fitting_line_3(covariance,c,line,k,diagonalize_traits); in linear_least_squares_fitting_3()
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/dports/math/openturns/openturns-1.18/python/src/ |
H A D | KarhunenLoeveReduction_doc.i.in | 13 Process trend, useful when the basis built using the covariance function 29 >>> covariance = ot.SquaredExponential() 30 >>> process = ot.GaussianProcess(covariance, mesh) 58 Process trend, useful when the basis built using the covariance function
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H A D | GeneralizedExponential_doc.i.in | 2 "Absolute exponential covariance function. 30 The *generalized exponential function* is a stationary covariance function with dimension :math:`d=… 52 Create a standard generalized exponential covariance function: 64 Create a generalized exponential covariance function specifying the scale vector and p: 69 Create a generalized exponential covariance function specifying the scale vector, the amplitude an…
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/dports/finance/quantlib/QuantLib-1.20/ql/methods/montecarlo/ |
H A D | genericlsregression.cpp | 57 Matrix covariance = stats.covariance(); in genericLongstaffSchwartzRegression() local 62 target[k] = covariance[k][N] + means[k]*means[N]; in genericLongstaffSchwartzRegression() 64 C[k][l] = C[l][k] = covariance[k][l] + means[k]*means[l]; in genericLongstaffSchwartzRegression()
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/dports/audio/sc3-plugins/sc3-plugins-Version-3.9.0/source/MCLDUGens/sc/HelpSource/Classes/ |
H A D | GaussClass.schelp | 30 [ // First class's mean, covariance, weight: 32 ],[ // Second class's mean, covariance, weight: 34 ],[ // Third class's mean, covariance, weight: 72 - N*N floats: the inverse of the covariance matrix; and 74 …the weight of the component divided by the square root of the determinant of the covariance matrix.
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/dports/math/octave-forge-stk/stk/inst/core/ |
H A D | stk_make_matcov.m | 1 % STK_MAKE_MATCOV computes a covariance matrix (and a design matrix) 5 % computes the covariance matrix K and the design matrix P for the model 13 % computes the covariance matrix K for the model MODEL between the sets 21 % noise variance is added on the diagonal of the covariance matrix). 53 % Check if the covariance model contains parameters 56 stk_error (['The covariance model contains undefined parameters, ' ... 74 %=== compute the covariance matrix
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/dports/science/py-OpenMC/openmc-0.12.2/openmc/data/ |
H A D | resonance_covariance.py | 188 cov = res_cov_range.covariance 212 res_cov_range.covariance = cov_subset 235 cov = self.covariance 339 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 343 self.covariance = covariance 532 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 534 super().__init__(energy_min, energy_max, parameters, covariance, mpar, 572 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 576 self.covariance = covariance
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/dports/science/py-GPy/GPy-1.10.0/doc/source/ |
H A D | tuto_plotting.rst | 15 will implement an example of a plotting function, which plots the covariance of a kernel. 22 For the covariance plot we define the function in :py:mod:`GPy.plotting.kernel_plots`. 32 Plot a kernel covariance w.r.t. another x. 47 First, we will write the necessary logic behind getting the covariance function. 48 This involves getting an Xgrid to plot with and the second x to compare the covariance to:: 61 from the visible_dims, ``Xgrid`` is the grid for the covariance, 63 ``X2`` for the kernel and ``K`` holds the kernel covariance for 82 plotting a mean function for the covariance plot as well. If you want to define your own defaults 96 … plots = dict(covariance=[pl().plot(canvas, Xgrid[:, free_dims], K, label=label, **kwargs)]) 100 plots = dict(covariance=[pl().contour(canvas, xx[:, 0], yy[0, :], [all …]
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/dports/science/openmc/openmc-0.12.2/openmc/data/ |
H A D | resonance_covariance.py | 188 cov = res_cov_range.covariance 212 res_cov_range.covariance = cov_subset 235 cov = self.covariance 339 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 343 self.covariance = covariance 532 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 534 super().__init__(energy_min, energy_max, parameters, covariance, mpar, 572 def __init__(self, energy_min, energy_max, parameters, covariance, mpar, argument 576 self.covariance = covariance
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/dports/math/openturns/openturns-1.18/python/doc/examples/probabilistic_modeling/stochastic_processes/ |
H A D | plot_userdefined_covariance_model.py | 33 covariance = ot.CovarianceMatrix(mesh.getVerticesNumber()) variable 38 covariance[k, l] = C(s[0], t[0]) 42 covmodel = ot.UserDefinedCovarianceModel(mesh, covariance)
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/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/segmentation/include/pcl/segmentation/ |
H A D | planar_region.h | 72 covariance_ = region.covariance; in PlanarRegion() 88 … PlanarRegion (const Eigen::Vector3f& centroid, const Eigen::Matrix3f& covariance, unsigned count, in PlanarRegion() argument 93 covariance_ = covariance; in PlanarRegion()
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/dports/math/openturns/openturns-1.18/lib/src/Base/Stat/ |
H A D | RankMCovarianceModel.cxx | 59 RankMCovarianceModel::RankMCovarianceModel(const CovarianceMatrix & covariance, in RankMCovarianceModel() argument 67 …if (!(covariance.getDimension() > 0)) throw InvalidArgumentException(HERE) << "Error: expected a c… in RankMCovarianceModel() 69 if (covariance.isDiagonal()) in RankMCovarianceModel() 71 variance_ = Point(covariance.getDimension()); in RankMCovarianceModel() 73 variance_[i] = covariance(i, i); in RankMCovarianceModel() 75 else covariance_ = covariance; in RankMCovarianceModel()
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/dports/math/openturns/openturns-1.18/python/test/ |
H A D | t_Normal_large.py | 31 covariance = oneSample.computeCovariance() variable 36 covariance[i, j] - sigma[i] * sigma[j] * R[i, j]) 84 covariance = oneSample.computeCovariance() variable 92 errorCovariance += fabs(covariance[i, j] - temp)
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/dports/multimedia/gstreamer1-libav/gst-libav-1.16.2/gst-libs/ext/libav/libavutil/ |
H A D | lls.c | 42 m->covariance[i][j] += var[i] * var[j]; in update_lls() 50 double (*factor)[MAX_VARS_ALIGN] = (void *) &m->covariance[1][0]; in avpriv_solve_lls() 51 double (*covar) [MAX_VARS_ALIGN] = (void *) &m->covariance[1][1]; in avpriv_solve_lls() 52 double *covar_y = m->covariance[0]; in avpriv_solve_lls()
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/dports/www/firefox-esr/firefox-91.8.0/media/ffvpx/libavutil/ |
H A D | lls.c | 42 m->covariance[i][j] += var[i] * var[j]; in update_lls() 50 double (*factor)[MAX_VARS_ALIGN] = (void *) &m->covariance[1][0]; in avpriv_solve_lls() 51 double (*covar) [MAX_VARS_ALIGN] = (void *) &m->covariance[1][1]; in avpriv_solve_lls() 52 double *covar_y = m->covariance[0]; in avpriv_solve_lls()
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/dports/multimedia/ffmpeg/ffmpeg-4.4.1/libavutil/ |
H A D | lls.c | 42 m->covariance[i][j] += var[i] * var[j]; in update_lls() 50 double (*factor)[MAX_VARS_ALIGN] = (void *) &m->covariance[1][0]; in avpriv_solve_lls() 51 double (*covar) [MAX_VARS_ALIGN] = (void *) &m->covariance[1][1]; in avpriv_solve_lls() 52 double *covar_y = m->covariance[0]; in avpriv_solve_lls()
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