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StatUtils.hh
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StatUtils.hh
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#ifndef NPSTAT_STATUTILS_HH_
#define NPSTAT_STATUTILS_HH_
/*!
// \file StatUtils.hh
//
// \brief Statistical utilities which did not end up in dedicated headers
//
// Author: I. Volobouev
//
// March 2010
*/
#include <vector>
namespace npstat {
/**
// This function calculates an empirical quantile
// from a _sorted_ vector of data points. If the "increaseRange"
// parameter is "true" then the value returned for x = 0.0
// will be smaller than data[0] and the value returned for
// x = 1.0 will be larger than the largest data value.
*/
template<typename Data>
Data empiricalQuantile(const std::vector<Data>& data, double x,
bool increaseRange=false);
/**
// The inverse to the npstat::empiricalQuantile (if there are no
// duplicate entries in the data). The data vector must be sorted.
*/
template<typename Data>
double empiricalCdf(const std::vector<Data>& data, const Data& x);
/**
// Find the bin number corresponding to the given cdf value in
// an array which represents a cumulative distribution function
// (the numbers in the array must increase). It is expected that
// the quantile is between cdf[0] and cdf[arrLen-1].
*/
template<typename Data>
unsigned quantileBinFromCdf(const Data* cdf, unsigned arrLen,
Data quantile, Data* remainder = 0);
/**
// This function returns the mathematical functional R(d^n f(x)/d x^n),
// where function f(x) is given by its tabulated values on a grid
// with constant distance h between points (it is assumed that each
// value is given in the middle of a cell, like in a histogram). The
// functional R(y(x)) is, by definition, the integral of y(x) squared.
// d^n f(x)/d x^n is the derivative of order n.
//
// Note that the table of function values is NOT preserved.
*/
template<typename Real>
Real squaredDerivativeIntegral(Real* fvalues, unsigned long arrLen,
unsigned n, Real h);
}
#include "npstat/stat/StatUtils.icc"
#endif // NPSTAT_STATUTILS_HH_

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