| /external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/ |
| LeastSquaresConverter.java | 39 * This class computes a possibly weighted squared sum of the residuals, which is
40 * a scalar value. The residuals are the difference between the theoretical model
49 * This class support combination of residuals with or without weights and correlations.
63 /** Observations to be compared to objective function to compute residuals. */
66 /** Optional weights for the residuals. */
69 /** Optional scaling matrix (weight and correlations) for the residuals. */
72 /** Build a simple converter for uncorrelated residuals with the same weight.
73 * @param function vectorial residuals function to wrap
74 * @param observations observations to be compared to objective function to compute residuals
84 /** Build a simple converter for uncorrelated residuals with the specific weights
163 final double[] residuals = function.value(point); local
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| MultipleLinearRegression.java | 26 * of <b>error terms</b> or <b>residuals</b>.
50 * Estimates the residuals, ie u = y - X*b.
52 * @return The [n,1] array representing the residuals
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| GLSMultipleLinearRegression.java | 130 RealVector residuals = calculateResiduals(); local
131 double t = residuals.dotProduct(getOmegaInverse().operate(residuals));
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| OLSMultipleLinearRegression.java | 143 * Returns the sum of squared residuals.
149 final RealVector residuals = calculateResiduals(); local
150 return residuals.dotProduct(residuals);
157 * where SSR is the {@link #calculateResidualSumOfSquares() sum of squared residuals}
171 * where SSR is the {@link #calculateResidualSumOfSquares() sum of squared residuals},
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| AbstractMultipleLinearRegression.java | 346 RealVector residuals = calculateResiduals(); local
347 return residuals.dotProduct(residuals) /
352 * Calculates the residuals of multiple linear regression in matrix
359 * @return The residuals [n,1] matrix
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/general/ |
| AbstractLeastSquaresOptimizer.java | 86 /** Current residuals. */
87 protected double[] residuals; field in class:AbstractLeastSquaresOptimizer
92 /** Weighted residuals */
95 /** Cost value (square root of the sum of the residuals). */
208 * Update the residuals array and cost function value.
229 residuals[i] = residual;
241 * mean of the square of all weighted residuals. This is related to the
253 * Get a Chi-Square-like value assuming the N residuals follow N
347 this.residuals = new double[target.length];
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| /frameworks/av/media/libstagefright/codecs/on2/h264dec/omxdl/reference/vc/m4p2/src/ |
| omxVCM4P2_TransRecBlockCoef_inter.c | 49 * pSrc -pointer to the residuals to be encoded; must be aligned on an
60 * pRec - pointer to the reconstructed texture residuals; must be aligned
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| omxVCM4P2_MCReconBlock.c | 193 * If prediction residuals are added then output intensities
220 * and the results of the inverse transformation (prediction residuals).
228 * residuals. If the pointer is NULL,then no prediction
234 * If prediction residuals are added then output intensities
276 * residuals; must be 16-byte aligned. If the pointer is NULL, then
286 * prediction residuals are added then output intensities are
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| omxVCM4P2_DecodeBlockCoef_Inter.c | 46 * clipping on each step) on the coefficients. The results (residuals) are
48 * buffer holds the residuals for further reconstruction.
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| omxVCM4P2_PredictReconCoefIntra.c | 50 * coefficient residuals (PQF) of the current block; must be
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/fitting/ |
| package.html | 25 were the objective function is the squared sum of residuals
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/estimation/ |
| AbstractEstimator.java | 66 /** Residuals array.
72 protected double[] residuals; field in class:AbstractEstimator
74 /** Cost value (square root of the sum of the residuals). */
147 * Update the residuals array and cost function value.
164 residuals[i] = FastMath.sqrt(wm.getWeight()) * residual;
174 * mean of the square of all weighted residuals. This is related to the
295 residuals = new double[rows];
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| GaussNewtonEstimator.java | 35 * squares criterion on the measurement residuals. It uses a
104 * values (square sum of the weighted residuals of considered measurements).
129 * values (square sum of the weighted residuals of considered measurements).
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| Estimator.java | 61 * mean of the square of all weighted residuals. This is related to the
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| LevenbergMarquardtEstimator.java | 284 qTy(residuals);
324 sum += jacobian[index] * residuals[i];
349 double[] tmpVec = residuals;
350 residuals = oldRes;
438 tmpVec = residuals;
439 residuals = oldRes;
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| /frameworks/av/media/libstagefright/codecs/on2/h264dec/omxdl/arm11/vc/m4p2/src/ |
| omxVCM4P2_DecodeBlockCoef_Inter.c | 46 * on the coefficients. The results (residuals) are placed in a contiguous array
47 * of 64 elements. For INTER block, the output buffer holds the residuals for
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| /frameworks/av/media/libstagefright/codecs/on2/h264dec/omxdl/arm_neon/vc/m4p2/src/ |
| omxVCM4P2_DecodeBlockCoef_Inter.c | 46 * on the coefficients. The results (residuals) are placed in a contiguous array
47 * of 64 elements. For INTER block, the output buffer holds the residuals for
|
| /cts/apps/CameraITS/tests/scene1/ |
| test_linearity.py | 103 line, residuals, _, _, _ = numpy.polyfit(range(len(sensitivities)),
105 print 'Line: m=%f, b=%f, resid=%f'%(line[0], line[1], residuals[0])
106 assert residuals[0] < RESIDUAL_THRESHOLD
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| /external/lmfit/lib/ |
| lmstruct.h | 59 int m_maxpri; /* -1, or max number of residuals to print. */
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| /external/webp/src/enc/ |
| predictor_enc.c | 280 // applied, quantizing residuals to multiples of quantization levels up to
325 uint32_t residuals[1 << MAX_TRANSFORM_BITS]; local
362 used_subtract_green, residuals);
364 UpdateHisto(histo_argb, residuals[relative_x]);
391 // Converts pixels of the image to residuals with respect to predictions.
393 // residuals to multiples of quantization levels up to max_quantization
426 // residuals before proceeding with the next row.
449 // Finds the best predictor for each tile, and converts the image to residuals
451 // near lossless processing, shaving off more bits of residuals for lower
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| cost_enc.h | 25 // On-the-fly info about the current set of residuals. Handy to avoid
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/analysis/interpolation/ |
| LoessInterpolator.java | 235 final double[] residuals = new double[n]; local
310 residuals[i] = FastMath.abs(yval[i] - res[i]);
324 System.arraycopy(residuals, 0, sortedResiduals, 0, n);
333 final double arg = residuals[i] / (6 * medianResidual);
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| /external/libopus/silk/ |
| NLSF_decode.c | 34 /* Predictive dequantizer for NLSF residuals */
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| /external/libvorbis/doc/ |
| vorbis.html | 85 <li><a href="residuals.html">MDCT-domain fine structure</a></li>
177 <li><a href="residuals.html">MDCT-domain fine structure</a>: Production,
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| /cts/tests/tests/location/src/android/location/cts/psedorange/ |
| Ecef2LlaConverter.java | 131 // calculate residuals in p and ecefZMeters
|
