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QuantLib: a free/open-source library for quantitative finance
Reference manual - version 1.40
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Statistics analysis of N-dimensional (sequence) data. More...
#include <ql/math/statistics/sequencestatistics.hpp>
Public Types | |
| typedef StatisticsType | statistics_type |
| typedef std::vector< typename StatisticsType::value_type > | value_type |
Public Member Functions | |
| GenericSequenceStatistics (Size dimension=0) | |
inspectors | |
| Size | size () const |
covariance and correlation | |
| Matrix | covariance () const |
| returns the covariance Matrix | |
| Matrix | correlation () const |
| returns the correlation Matrix | |
1-D inspectors lifted from underlying statistics class | |
| Size | samples () const |
| Real | weightSum () const |
N-D inspectors lifted from underlying statistics class | |
| std::vector< Real > | mean () const |
| std::vector< Real > | variance () const |
| std::vector< Real > | standardDeviation () const |
| std::vector< Real > | downsideVariance () const |
| std::vector< Real > | downsideDeviation () const |
| std::vector< Real > | semiVariance () const |
| std::vector< Real > | semiDeviation () const |
| std::vector< Real > | errorEstimate () const |
| std::vector< Real > | skewness () const |
| std::vector< Real > | kurtosis () const |
| std::vector< Real > | min () const |
| std::vector< Real > | max () const |
| std::vector< Real > | gaussianPercentile (Real y) const |
| std::vector< Real > | percentile (Real y) const |
| std::vector< Real > | gaussianPotentialUpside (Real percentile) const |
| std::vector< Real > | potentialUpside (Real percentile) const |
| std::vector< Real > | gaussianValueAtRisk (Real percentile) const |
| std::vector< Real > | valueAtRisk (Real percentile) const |
| std::vector< Real > | gaussianExpectedShortfall (Real percentile) const |
| std::vector< Real > | expectedShortfall (Real percentile) const |
| std::vector< Real > | regret (Real target) const |
| std::vector< Real > | gaussianShortfall (Real target) const |
| std::vector< Real > | shortfall (Real target) const |
| std::vector< Real > | gaussianAverageShortfall (Real target) const |
| std::vector< Real > | averageShortfall (Real target) const |
Modifiers | |
| Size | dimension_ = 0 |
| std::vector< statistics_type > | stats_ |
| std::vector< Real > | results_ |
| Matrix | quadraticSum_ |
| void | reset (Size dimension=0) |
| template<class Sequence> | |
| void | add (const Sequence &sample, Real weight=1.0) |
| template<class Iterator> | |
| void | add (Iterator begin, Iterator end, Real weight=1.0) |
Statistics analysis of N-dimensional (sequence) data.
It provides 1-dimensional statistics as discrepancy plus N-dimensional (sequence) statistics (e.g. mean, variance, skewness, kurtosis, etc.) with one component for each dimension of the sample space.
For most of the statistics this class relies on the StatisticsType underlying class to provide 1-D methods that will be iterated for all the components of the N-D data. These lifted methods are the union of all the methods that might be requested to the 1-D underlying StatisticsType class, with the usual compile-time checks provided by the template approach.