/frameworks/av/media/libcpustats/ |
CentralTendencyStatistics.cpp | 52 double CentralTendencyStatistics::variance() const function in class:CentralTendencyStatistics 54 double variance; local 58 variance = mM2 / (mN - 1); 60 variance = NAN; 62 mVariance = variance; 65 variance = mVariance; 67 return variance; 74 stddev = sqrt(variance());
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
StandardDeviation.java | 26 * is the positive square root of the variance. This implementation wraps a 27 * {@link Variance} instance. The <code>isBiasCorrected</code> property of the 28 * wrapped Variance instance is exposed, so that this class can be used to 30 * bias-corrected "sample variance") or the "population standard deviation" 31 * (the square root of the non-bias-corrected "population variance"). See 32 * {@link Variance} for more information. 47 /** Wrapped Variance instance */ 48 private Variance variance = null; field in class:StandardDeviation 51 * Constructs a StandardDeviation. Sets the underlying {@link Variance} [all...] |
Variance.java | 27 * Computes the variance of the available values. By default, the unbiased 28 * "sample variance" definitional formula is used: 30 * variance = sum((x_i - mean)^2) / (n - 1) </p> 38 * <li> The <code>getResult</code> method computes the variance using 46 * Chan, Golub, Levesque, <i>Algorithms for Computing the Sample Variance</i>, 54 * The "population variance" ( sum((x_i - mean)^2) / n ) can also 68 public class Variance extends AbstractStorelessUnivariateStatistic implements Serializable, WeightedEvaluation { 73 /** SecondMoment is used in incremental calculation of Variance*/ 77 * Boolean test to determine if this Variance should also increment 78 * the second moment, this evaluates to false when this Variance i [all...] |
Kurtosis.java | 111 double variance = moment.m2 / (moment.n - 1); local 112 if (moment.n <= 3 || variance < 10E-20) { 119 ((n - 1) * (n -2) * (n -3) * variance * variance); 171 Variance variance = new Variance(); local 172 variance.incrementAll(values, begin, length); 173 double mean = variance.moment.m1; 174 double stdDev = FastMath.sqrt(variance.getResult()) [all...] |
Skewness.java | 107 double variance = moment.m2 / (moment.n - 1); local 108 if (variance < 10E-20) { 113 ((n0 - 1) * (n0 -2) * FastMath.sqrt(variance) * variance); 172 final double variance = (accum - (accum2 * accum2 / length)) / (length - 1); local 179 accum3 /= variance * FastMath.sqrt(variance);
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/external/guava/guava-tests/benchmark/com/google/common/math/ |
StatsBenchmark.java | 28 * Benchmarks for various algorithms for computing the mean and/or variance. 75 private final double variance; field in class:StatsBenchmark.MeanAndVariance 77 MeanAndVariance(double mean, double variance) { 79 this.variance = variance; 84 return Doubles.hashCode(mean) * 31 + Doubles.hashCode(variance); 91 MeanAndVariance variance(double[] values, MeanAlgorithm meanAlgorithm) { method 97 MeanAndVariance variance(double[] values, MeanAlgorithm meanAlgorithm) { method 109 MeanAndVariance variance(double[] values, MeanAlgorithm meanAlgorithm) { method 126 MeanAndVariance variance(double[] values, MeanAlgorithm meanAlgorithm) method 141 abstract MeanAndVariance variance(double[] values, MeanAlgorithm meanAlgorithm); method in class:StatsBenchmark.VarianceAlgorithm [all...] |
/tools/test/connectivity/acts/tests/google/wifi/ |
WifiNewSetupAutoJoinTest.py | 167 variance = 5 168 attn_value = [att0 + variance * 2, att1, att2, att3] 175 variance = 5 176 attn_value = [att0 + variance, att1, att2, att3] 183 variance = 5 191 variance = 5 192 attn_value = [att0 - variance, att1, att2, att3] 206 variance = 5 207 attn_value = [att0 + variance * 2, att1, att2, attn3] 214 variance = [all...] |
WifiAutoJoinTest.py | 183 variance = 5 184 attenuations = ([att0 + variance * 2, att1, att2], 185 [att0 + variance, att1, att2], [att0, att1, att2], 186 [att0 - variance, att1, att2]) 207 variance = 5 208 attenuations = ([att0 + variance * 2, att1, att2], 209 [att0 + variance, att1, att2], [att0, att1, att2]) 230 variance = 5 231 attenuations = ([att0 - variance, att1 + variance, att2] [all...] |
/external/libmpeg2/common/ |
icv_variance.c | 26 * This file contains the functions to compute variance 60 * Computes variance of a given 8x4 block 63 * Compute variance of a given 8x4 block 78 * Variance 104 /* variance */ 110 /* calculates the variance only for field area not frame one. */
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/external/autotest/server/tests/netpipe/ |
control.srv | 19 variance - NetPIPE chooses the message sizes at regular intervals, 32 variance = 17 36 upper_bound=upper_bound, variance=variance)
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control.stress.srv | 21 variance - NetPIPE chooses the message sizes at regular intervals, 43 variance = 17 50 upper_bound=upper_bound, variance=variance)
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
StatisticalSummaryValues.java | 38 /** The sample variance */ 39 private final double variance; field in class:StatisticalSummaryValues 57 * @param variance the sample variance 63 public StatisticalSummaryValues(double mean, double variance, long n, 67 this.variance = variance; 113 return FastMath.sqrt(variance); 117 * @return Returns the variance. 120 return variance; [all...] |
SummaryStatistics.java | 26 import org.apache.commons.math.stat.descriptive.moment.Variance; 45 * default implementation for the variance can be overridden by calling 67 /** SecondMoment is used to compute the mean and variance */ 91 /** variance of values that have been added */ 92 protected Variance variance = new Variance(); field in class:SummaryStatistics 115 /** Variance statistic implementation - can be reset by setter. */ 116 private StorelessUnivariateStatistic varianceImpl = variance; 154 // If mean, variance or geomean have been overridden [all...] |
/external/webrtc/webrtc/modules/audio_processing/intelligibility/ |
intelligibility_utils_unittest.cc | 71 // Tests VarianceArray, for all variance step types. 87 EXPECT_EQ(0, variance_array.variance()[0]); 90 EXPECT_EQ(0, variance_array.variance()[0]); 100 EXPECT_GE(variance_array.variance()[j], 0.0f); 101 EXPECT_LE(variance_array.variance()[j], 1.0f); 105 EXPECT_EQ(0, variance_array.variance()[0]); 141 EXPECT_EQ(0, variance_array.variance()[j]); 143 EXPECT_NEAR(kTestVarianceBufferNotFull, variance_array.variance()[j], 146 EXPECT_NEAR(kTestVarianceBufferFull1, variance_array.variance()[j], 149 EXPECT_NEAR(kTestVarianceBufferFull2, variance_array.variance()[j] [all...] |
/external/webrtc/webrtc/modules/audio_processing/test/ |
test_utils.h | 107 float ComputeSNR(const T* ref, const T* test, size_t length, float* variance) { 110 *variance = 0; 114 *variance += ref[i] * ref[i]; 118 *variance /= length; 120 *variance -= mean * mean; 124 snr = 10 * log10(*variance / mse);
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/frameworks/av/media/libcpustats/include/cpustats/ |
CentralTendencyStatistics.h | 45 // return the variance of all samples so far 46 double variance() const; 65 // cached variance, and n at time of caching
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
MultipleLinearRegression.java | 43 * Estimates the variance of the regression parameters, ie Var(b). 45 * @return The [k,k] array representing the variance of b 57 * Returns the variance of the regressand, ie Var(y). 59 * @return The double representing the variance of y
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GLSMultipleLinearRegression.java | 36 * whose variance is 103 * Calculates the variance on the beta. 107 * @return The beta variance matrix 118 * Calculates the estimated variance of the error term using the formula 125 * @return error variance
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/external/webrtc/webrtc/test/ |
statistics.cc | 31 double Statistics::Variance() const { 38 return sqrt(Variance());
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/device/google/contexthub/firmware/os/algos/calibration/gyroscope/ |
gyro_stillness_detect.h | 23 * is computed using non-overlapping windows of signal variance 48 // Variance threshold for the stillness confidence score. 51 // Delta about the variance threshold for calculation of the 72 // variance for the current window (used for stillness detection). 81 // Latest computed variance.
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gyro_stillness_detect.c | 33 // Set the delta about the variance threshold for calculation 41 // Set the variance threshold parameter for the stillness 58 // online mean and variance statistics: 87 // Reset current window mean and variance. 106 // Online window mean and variance ("one-pass" accumulation). 137 // Update the final calculation of window mean and variance. 161 // Define the variance thresholds. 172 // Sensor variance exceeds the upper threshold (i.e., motion detected). 180 // Sensor variance is below the lower threshold (i.e., stillness
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/external/autotest/client/site_tests/video_WebRtcCamera/ |
ssim.js | 29 // square root. The latter is actually an unbiased estimate of the variance, 30 // not the exact variance. 43 return {mean : meanA, variance : accu / a.length}; 70 var sigmaX2 = statsX.variance; 74 var sigmaY2 = statsY.variance;
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/external/autotest/client/site_tests/video_WebRtcPeerConnectionWithCamera/ |
ssim.js | 29 // square root. The latter is actually an unbiased estimate of the variance, 30 // not the exact variance. 43 return {mean : meanA, variance : accu / a.length}; 70 var sigmaX2 = statsX.variance; 74 var sigmaY2 = statsY.variance;
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/external/libmpeg2/common/x86/ |
icv_variance_ssse3.c | 26 * This file contains the functions to compute variance 60 * Computes variance of a given 8x4 block 63 * Compute variance of a given 8x4 block 78 * Variance 153 /* Compute variance */
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/cts/apps/CameraITS/tests/scene1/ |
test_dng_noise_model.py | 25 DIFF_THRESH = 0.0005 # absolute variance delta threshold 26 FRAC_THRESH = 0.2 # relative variance delta threshold 35 # defined as being within an absolute variance delta or relative variance 36 # delta of the expected variance, whichever is larger. This is to allow the 92 # non-uniform lighting or vignetting doesn't affect the variance 116 pylab.ylabel('Center patch variance')
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