| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| Mean.java | 26 * <p>Computes the arithmetic mean of a set of values. Uses the definitional
29 * mean = sum(x_i) / n
42 * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
45 * correcting this by adding the mean deviation of the data values from the
46 * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
59 public class Mean extends AbstractStorelessUnivariateStatistic
76 /** Constructs a Mean. */
77 public Mean() {
83 * Constructs a Mean with an External Moment.
87 public Mean(final FirstMoment m1)
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| VectorialMean.java | 25 * Returns the arithmetic mean of the available vectors.
35 private final Mean[] means;
41 means = new Mean[dimension];
43 means[i] = new Mean();
62 * Get the mean vector.
63 * @return mean vector
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| Skewness.java | 29 * skewness = [n / (n -1) (n - 2)] sum[(x_i - mean)^3] / std^3 </p>
31 * where n is the number of values, mean is the {@link Mean} and std is the
158 Mean mean = new Mean(); local
159 // Get the mean and the standard deviation
160 double m = mean.evaluate(values, begin, length);
164 // a duplicate pass to get the mean
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| Variance.java | 30 * variance = sum((x_i - mean)^2) / (n - 1) </p>
32 * where mean is the {@link Mean} and <code>n</code> is the number
54 * The "population variance" ( sum((x_i - mean)^2) / n ) can also
252 Mean mean = new Mean(); local
253 double m = mean.evaluate(values, begin, length);
268 * where weightedMean is the weighted mean</p>
312 Mean mean = new Mean() local
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| SemiVariance.java | 36 * <p>The cutoff value defaults to the mean, bias correction defaults to <code>true</code>
169 * This method calculates {@link SemiVariance} for the entire array against the mean, using
187 * <p>Returns the {@link SemiVariance} of the designated values against the mean, using
202 double m = (new Mean()).evaluate(values, start, length);
208 * This method calculates {@link SemiVariance} for the entire array against the mean, using
218 double m = (new Mean()).evaluate(values);
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| /frameworks/base/media/mca/filterfw/native/core/ |
| statistics.h | 31 float Mean() const { return mean_; }
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| /cts/apps/CtsVerifier/src/com/android/cts/verifier/audio/ |
| Util.java | 4 import org.apache.commons.math.stat.descriptive.moment.Mean;
22 * Calculate mean of data.
24 public static double mean(double[] data) { method in class:Util
25 Mean mean = new Mean(); local
26 return mean.evaluate(data);
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/correlation/ |
| Covariance.java | 23 import org.apache.commons.math.stat.descriptive.moment.Mean;
38 * where <code>E(X)</code> is the mean of <code>X</code> and <code>E(Y)</code>
39 * is the mean of the <code>Y</code> values.
222 Mean mean = new Mean(); local
232 double xMean = mean.evaluate(xArray);
233 double yMean = mean.evaluate(yArray);
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| /art/runtime/base/ |
| histogram.h | 27 // Histogram analysis goes beyond simple mean and standard deviation to provide
57 double Mean() const;
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| histogram-inl.h | 137 template <class Value> inline double Histogram<Value>::Mean() const {
193 const TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust);
198 << "Avg: " << FormatDuration(Mean() * kAdjust, unit, kFractionalDigits) << " Max: "
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| histogram_test.cc | 39 double mean; local
43 mean = hist->Mean();
44 EXPECT_DOUBLE_EQ(mean, 50.0);
50 mean = hist->Mean();
51 EXPECT_DOUBLE_EQ(20.5, mean);
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
| SummaryStatistics.java | 24 import org.apache.commons.math.stat.descriptive.moment.Mean;
67 /** SecondMoment is used to compute the mean and variance */
88 /** mean of values that have been added */
89 protected Mean mean = new Mean(); field in class:SummaryStatistics
109 /** Geometric mean statistic implementation - can be reset by setter. */
112 /** Mean statistic implementation - can be reset by setter. */
113 private StorelessUnivariateStatistic meanImpl = mean;
154 // If mean, variance or geomean have been overridden
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| DescriptiveStatistics.java | 27 import org.apache.commons.math.stat.descriptive.moment.Mean;
81 /** Mean statistic implementation - can be reset by setter. */
82 private UnivariateStatistic meanImpl = new Mean();
84 /** Geometric mean statistic implementation - can be reset by setter. */
190 * arithmetic mean </a> of the available values
191 * @return The mean or Double.NaN if no values have been added.
199 * geometric mean </a> of the available values
432 outBuffer.append("mean: ").append(getMean()).append(endl);
453 * Returns the currently configured mean implementation.
455 * @return the UnivariateStatistic implementing the mean
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| MultivariateSummaryStatistics.java | 27 import org.apache.commons.math.stat.descriptive.moment.Mean;
45 * For example, the default implementation for the mean can be overridden by
97 /** Geometric mean statistic implementation - can be reset by setter. */
100 /** Mean statistic implementation - can be reset by setter. */
131 meanImpl[i] = new Mean();
226 * Returns an array whose i<sup>th</sup> entry is the mean of the
290 * Returns an array whose i<sup>th</sup> entry is the geometric mean of the
315 append(outBuffer, getMean(), "mean: ", separator, suffix);
316 append(outBuffer, getGeometricMean(), "geometric mean: ", separator, suffix);
561 * Returns the currently configured geometric mean implementatio
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/ |
| StatUtils.java | 24 import org.apache.commons.math.stat.descriptive.moment.Mean;
60 /** mean */
61 private static final UnivariateStatistic MEAN = new Mean();
69 /** geometric mean */
222 * Returns the arithmetic mean of the entries in the input array, or
227 * See {@link org.apache.commons.math.stat.descriptive.moment.Mean} for
231 * @return the mean of the values or Double.NaN if the array is empty
234 public static double mean(final double[] values) { method in class:StatUtils
235 return MEAN.evaluate(values)
255 public static double mean(final double[] values, final int begin, method in class:StatUtils
650 double mean = stats.getMean(); local
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| /external/opencv/cxcore/src/ |
| cxmean.cpp | 46 * Mean value over the region *
165 mean[0] = scale*(double)tmp##0
171 mean[0] = t0; \
172 mean[1] = t1
179 mean[0] = t0; \
180 mean[1] = t1; \
181 mean[2] = t2
187 mean[0] = t0; \
188 mean[1] = t1; \
191 mean[2] = t0;
384 CvScalar mean = {{0,0,0,0}}; local
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