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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/docs/KeywordMetadata/
H A Dmethod-bayes_calibration-queso30 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…
H A Dmodel-random_field4 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
/dports/science/InsightToolkit/ITK-5.0.1/Testing/Data/Input/Statistics/
H A DTwoDimensionTwoGaussian.Readme23 covariance
30 covariance
37 covariance
45 covariance
/dports/multimedia/chilitags/chilitags-2.0.0-169-g0d9854f/src/
H A DEstimatePose3D.cpp81 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()
/dports/math/R-cran-pls/pls/tests/RUnit/common/
H A Drunit.jackknife.R17 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)),
/dports/science/gnudatalanguage/gdl-1.0.1/src/pro/
H A Da_correlate.pro16 ; /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 $
/dports/math/scilab/scilab-6.1.1/scilab/modules/statistics/macros/
H A Dcov.sci15 // 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]
/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/queso/src/stats/src/
H A DGaussianLikelihoodDiagonalCovariance.C37 const V & observations, const V & covariance) in GaussianLikelihoodDiagonalCovariance() argument
39 m_covariance(covariance) in GaussianLikelihoodDiagonalCovariance()
41 if (covariance.sizeLocal() != observations.sizeLocal()) { in GaussianLikelihoodDiagonalCovariance()
H A DGaussianLikelihoodFullCovariance.C37 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()
/dports/math/cgal/CGAL-5.3/include/CGAL/
H A Dlinear_least_squares_fitting_triangles_3.h53 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()
/dports/math/openturns/openturns-1.18/python/src/
H A DKarhunenLoeveReduction_doc.i.in13 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
H A DGeneralizedExponential_doc.i.in2 "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…
/dports/finance/quantlib/QuantLib-1.20/ql/methods/montecarlo/
H A Dgenericlsregression.cpp57 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()
/dports/audio/sc3-plugins/sc3-plugins-Version-3.9.0/source/MCLDUGens/sc/HelpSource/Classes/
H A DGaussClass.schelp30 [ // 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.
/dports/math/octave-forge-stk/stk/inst/core/
H A Dstk_make_matcov.m1 % 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
/dports/science/py-OpenMC/openmc-0.12.2/openmc/data/
H A Dresonance_covariance.py188 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
/dports/science/py-GPy/GPy-1.10.0/doc/source/
H A Dtuto_plotting.rst15 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 …]
/dports/science/openmc/openmc-0.12.2/openmc/data/
H A Dresonance_covariance.py188 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
/dports/math/openturns/openturns-1.18/python/doc/examples/probabilistic_modeling/stochastic_processes/
H A Dplot_userdefined_covariance_model.py33 covariance = ot.CovarianceMatrix(mesh.getVerticesNumber()) variable
38 covariance[k, l] = C(s[0], t[0])
42 covmodel = ot.UserDefinedCovarianceModel(mesh, covariance)
/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/segmentation/include/pcl/segmentation/
H A Dplanar_region.h72 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()
/dports/math/openturns/openturns-1.18/lib/src/Base/Stat/
H A DRankMCovarianceModel.cxx59 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()
/dports/math/openturns/openturns-1.18/python/test/
H A Dt_Normal_large.py31 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)
/dports/multimedia/gstreamer1-libav/gst-libav-1.16.2/gst-libs/ext/libav/libavutil/
H A Dlls.c42 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()
/dports/www/firefox-esr/firefox-91.8.0/media/ffvpx/libavutil/
H A Dlls.c42 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()
/dports/multimedia/ffmpeg/ffmpeg-4.4.1/libavutil/
H A Dlls.c42 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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