QuantLib_GenericSequenceStatistics (3) - Linux Manuals

QuantLib_GenericSequenceStatistics: Statistics analysis of N-dimensional (sequence) data.

Command to display QuantLib_GenericSequenceStatistics manual in Linux: $ man 3 QuantLib_GenericSequenceStatistics

NAME

QuantLib::GenericSequenceStatistics - Statistics analysis of N-dimensional (sequence) data.

SYNOPSIS

#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

Disposable< Matrix > covariance () const
returns the covariance Matrix
Disposable< 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

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)

Protected Attributes

Size dimension_

std::vector< statistics_type > stats_

std::vector< Real > results_

Matrix quadraticSum_

Detailed Description

template<class StatisticsType> class QuantLib::GenericSequenceStatistics< StatisticsType >

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.

Tests

: the correctness of the returned values is tested by checking them against numerical calculations.

Author

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