IncrementalStatistics Class Reference#include <incrementalstatistics.hpp>
List of all members.
Detailed Description
Statistics tool based on incremental accumulation.
It can accumulate a set of data and return statistics (e.g: mean, variance, skewness, kurtosis, error estimation, etc.)
- Warning:
- high moments are numerically unstable for high average/standardDeviation ratios
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Public Member Functions |
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Size | samples () const |
| number of samples collected
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double | weightSum () const |
| sum of data weights
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double | mean () const |
double | variance () const |
double | standardDeviation () const |
double | downsideVariance () const |
double | downsideDeviation () const |
double | errorEstimate () const |
double | skewness () const |
double | kurtosis () const |
double | min () const |
double | max () const |
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void | add (double value, double weight=1.0) |
| adds a datum to the set, possibly with a weight
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template<class DataIterator> void | addSequence (DataIterator begin, DataIterator end) |
| adds a sequence of data to the set, with default weight
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template<class DataIterator, class WeightIterator> void | addSequence (DataIterator begin, DataIterator end, WeightIterator wbegin) |
| adds a sequence of data to the set, each with its weight
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void | reset () |
| resets the data to a null set
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Protected Attributes |
Size | sampleNumber_ |
Size | downsideSampleNumber_ |
double | sampleWeight_ |
double | downsideSampleWeight_ |
double | sum_ |
double | quadraticSum_ |
double | downsideQuadraticSum_ |
double | cubicSum_ |
double | fourthPowerSum_ |
double | min_ |
double | max_ |
Member Function Documentation
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returns the mean, defined as
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double variance |
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const |
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returns the variance, defined as
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double standardDeviation |
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const |
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returns the standard deviation , defined as the square root of the variance. |
double downsideVariance |
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const |
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returns the downside variance, defined as
, where = 0 if x > 0 and =1 if x <0 |
double downsideDeviation |
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const |
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returns the downside deviation, defined as the square root of the downside variance. |
double errorEstimate |
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const |
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returns the error estimate , defined as the square root of the ratio of the variance to the number of samples. |
double skewness |
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const |
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returns the skewness, defined as
The above evaluates to 0 for a Gaussian distribution. |
double kurtosis |
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const |
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returns the excess kurtosis, defined as
The above evaluates to 0 for a Gaussian distribution. |
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returns the minimum sample value |
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returns the maximum sample value |
void add |
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double |
value, |
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double |
weight = 1.0 |
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adds a datum to the set, possibly with a weight
- Precondition:
- weights must be positive or null
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The documentation for this class was generated from the following files:
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