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QuantLib_IncrementalStatistics
Langue: en
Version: 375310 (fedora - 01/12/10)
Section: 3 (Bibliothèques de fonctions)
Sommaire
- NAME
- SYNOPSIS
- Detailed Description
- Member Function Documentation
- Real mean () constreturns the mean, defined as [
- ngle = ac{um w_i x_i}{um w_i}. ]
- Real variance () constreturns the variance, defined as [ ac{N}{N-1}
- . ]
- Real standardDeviation () constreturns the standard deviation $ igma $, defined as the square root of the variance.
- Real errorEstimate () constreturns the error estimate $ \psilon $, defined as the square root of the ratio of the variance to the number of samples.
- Real skewness () constreturns the skewness, defined as [ ac{N^2}{(N-1)(N-2)} ac{
- }{igma^3}. ] The above evaluates to 0 for a Gaussian distribution.
- Real kurtosis () constreturns the excess kurtosis, defined as [ ac{N^2(N+1)}{(N-1)(N-2)(N-3)} ac{
- }{igma^4} - ac{3(N-1)^2}{(N-2)(N-3)}. ] The above evaluates to 0 for a Gaussian distribution.
- Real min () constreturns the minimum sample value
- Real max () constreturns the maximum sample value
- Real downsideVariance () constreturns the downside variance, defined as [ ac{N}{N-1} imes ac{ um_{i=1}^{N} heta imes x_i^{2}}{ um_{i=1}^{N} w_i} ], where $ heta $ = 0 if x > 0 and $ heta $ =1 if x <0
- Real downsideDeviation () constreturns the downside deviation, defined as the square root of the downside variance.
- void add (Real value, Real weight = 1.0)
- void addSequence (DataIterator begin, DataIterator end, WeightIterator wbegin)
- Author
NAME
QuantLib::IncrementalStatistics -Statistics tool based on incremental accumulation.
SYNOPSIS
#include <ql/math/statistics/incrementalstatistics.hpp>
Public Types
typedef Real value_type
Public Member Functions
Inspectors
Size samples () const
number of samples collected
Real weightSum () const
sum of data weights
Real mean () const
Real variance () const
Real standardDeviation () const
Real errorEstimate () const
Real skewness () const
Real kurtosis () const
Real min () const
Real max () const
Real downsideVariance () const
Real downsideDeviation () const
Modifiers
void add (Real value, Real weight=1.0)
adds a datum to the set, possibly with a weight
template<class DataIterator > void addSequence (DataIterator begin, DataIterator end)
adds a sequence of data to the set, with default weight
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
void reset ()
resets the data to a null set
Protected Attributes
Size sampleNumber_
Size downsideSampleNumber_
Real sampleWeight_
Real downsideSampleWeight_
Real sum_
Real quadraticSum_
Real downsideQuadraticSum_
Real cubicSum_
Real fourthPowerSum_
Real min_
Real max_
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.
Member Function Documentation
Real mean () constreturns the mean, defined as [
ngle = ac{um w_i x_i}{um w_i}. ]
Real variance () constreturns the variance, defined as [ ac{N}{N-1}
. ]
Real standardDeviation () constreturns the standard deviation $ igma $, defined as the square root of the variance.
Real errorEstimate () constreturns the error estimate $ \psilon $, defined as the square root of the ratio of the variance to the number of samples.
Real skewness () constreturns the skewness, defined as [ ac{N^2}{(N-1)(N-2)} ac{
}{igma^3}. ] The above evaluates to 0 for a Gaussian distribution.
Real kurtosis () constreturns the excess kurtosis, defined as [ ac{N^2(N+1)}{(N-1)(N-2)(N-3)} ac{
}{igma^4} - ac{3(N-1)^2}{(N-2)(N-3)}. ] The above evaluates to 0 for a Gaussian distribution.
Real min () constreturns the minimum sample value
Real max () constreturns the maximum sample value
Real downsideVariance () constreturns the downside variance, defined as [ ac{N}{N-1} imes ac{ um_{i=1}^{N} heta imes x_i^{2}}{ um_{i=1}^{N} w_i} ], where $ heta $ = 0 if x > 0 and $ heta $ =1 if x <0
Real downsideDeviation () constreturns the downside deviation, defined as the square root of the downside variance.
void add (Real value, Real weight = 1.0)
adds a datum to the set, possibly with a weight Precondition:
- weight must be positive or null
void addSequence (DataIterator begin, DataIterator end, WeightIterator wbegin)
adds a sequence of data to the set, each with its weight Precondition:
- weights must be positive or null
Author
Generated automatically by Doxygen for QuantLib from the source code.
- NAME
- SYNOPSIS
-
- Public Types
- Public Member Functions
- Protected Attributes
- Detailed Description
- Member Function Documentation
-
- Real mean () constreturns the mean, defined as [
-
- ngle = ac{um w_i x_i}{um w_i}. ]
- Real variance () constreturns the variance, defined as [ ac{N}{N-1}
-
- . ]
- Real standardDeviation () constreturns the standard deviation $ igma $, defined as the square root of the variance.
- Real errorEstimate () constreturns the error estimate $ \psilon $, defined as the square root of the ratio of the variance to the number of samples.
- Real skewness () constreturns the skewness, defined as [ ac{N^2}{(N-1)(N-2)} ac{
-
- }{igma^3}. ] The above evaluates to 0 for a Gaussian distribution.
- Real kurtosis () constreturns the excess kurtosis, defined as [ ac{N^2(N+1)}{(N-1)(N-2)(N-3)} ac{
-
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