Searched defs:covariance (Results 1 - 7 of 7) sorted by relevance

/external/apache-commons-math/src/main/java/org/apache/commons/math/random/
H A DCorrelatedRandomVectorGenerator.java32 * definite covariance matrix.</p>
43 * <p>Sometimes, the covariance matrix for a given simulation is not
47 * of the covariance matrix should not be negative either, they
50 * where <code>C</code> is the covariance matrix and <code>U</code>
54 * the rank of the covariance matrix, and it is the dimension of the
75 /** Permutated Cholesky root of the covariance matrix. */
78 /** Rank of the covariance matrix. */
83 * vector and covariance matrix.</p>
85 * @param covariance covariance matri
97 CorrelatedRandomVectorGenerator(double[] mean, RealMatrix covariance, double small, NormalizedRandomGenerator generator) argument
126 CorrelatedRandomVectorGenerator(RealMatrix covariance, double small, NormalizedRandomGenerator generator) argument
188 decompose(RealMatrix covariance, double small) argument
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/correlation/
H A DCovariance.java30 * <code>double[][]</code> arguments generate covariance matrices. The
48 /** covariance matrix */
52 * Create an empty covariance matrix.
71 * covariance estimates are bias-corrected.</p>
101 * Create a covariance matrix from a matrix whose columns
105 * covariance estimates are bias-corrected.</p>
121 * Create a covariance matrix from a matrix whose columns
135 * Returns the covariance matrix
137 * @return covariance matrix
154 * Compute a covariance matri
220 public double covariance(final double[] xArray, final double[] yArray, boolean biasCorrected) method in class:Covariance
255 public double covariance(final double[] xArray, final double[] yArray) method in class:Covariance
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H A DPearsonsCorrelation.java89 * matrix is computed by scaling the Covariance's covariance matrix.
93 * @param covariance Covariance instance
95 public PearsonsCorrelation(Covariance covariance) { argument
96 RealMatrix covarianceMatrix = covariance.getCovarianceMatrix();
100 nObs = covariance.getN();
105 * Create a PearsonsCorrelation from a covariance matrix. The correlation
106 * matrix is computed by scaling the covariance matrix.
108 * @param covarianceMatrix covariance matrix
110 * the covariance matrix
244 * Derives a correlation matrix from a covariance matri
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/
H A DGLSMultipleLinearRegression.java27 * GLS assumes a general covariance matrix Omega of the error
48 /** Inverse of covariance matrix. */
54 * @param covariance array representing the covariance matrix
56 public void newSampleData(double[] y, double[][] x, double[][] covariance) { argument
60 validateCovarianceData(x, covariance);
61 newCovarianceData(covariance);
65 * Add the covariance data.
67 * @param omega the [n,n] array representing the covariance
75 * Get the inverse of the covariance
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H A DAbstractMultipleLinearRegression.java223 * Validates that the x data and covariance matrix have the same
224 * number of rows and that the covariance matrix is square.
227 * @param covariance the [n,n] array representing the covariance matrix
229 * to the number of rows in covariance or covariance is not square.
231 protected void validateCovarianceData(double[][] x, double[][] covariance) { argument
232 if (x.length != covariance.length) {
234 LocalizedFormats.DIMENSIONS_MISMATCH_SIMPLE, x.length, covariance.length);
236 if (covariance
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/external/ceres-solver/internal/ceres/
H A Dcovariance_test.cc31 #include "ceres/covariance.h"
288 // covariance computation is correct.
315 Covariance covariance(options);
316 EXPECT_TRUE(covariance.Compute(covariance_blocks, &problem_));
322 GetCovarianceBlockAndCompare(block1, block2, covariance, expected_covariance);
324 GetCovarianceBlockAndCompare(block2, block1, covariance, expected_covariance);
331 const Covariance& covariance,
339 EXPECT_TRUE(covariance.GetCovarianceBlock(block1,
743 Covariance covariance(options);
744 EXPECT_TRUE(covariance
329 GetCovarianceBlockAndCompare(const double* block1, const double* block2, const Covariance& covariance, const double* expected_covariance) argument
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/external/ImageMagick/coders/
H A Ddds.c1370 static void ComputePrincipleComponent(const float *covariance,
1382 row0.x = covariance[0];
1383 row0.y = covariance[1];
1384 row0.z = covariance[2];
1387 row1.x = covariance[1];
1388 row1.y = covariance[3];
1389 row1.z = covariance[4];
1392 row2.x = covariance[2];
1393 row2.y = covariance[4];
1394 row2.z = covariance[
1368 ComputePrincipleComponent(const float *covariance, DDSVector3 *principle) argument
1431 ComputeWeightedCovariance(const size_t count, const DDSVector4 *points, float *covariance) argument
2525 covariance[16]; local
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