errorprop.h File Reference

Automatic propagation of uncertainties on arbitrary functions. More...

#include "../core/core_traits.h"
#include "../algebra/vec.h"
#include "../autodiff/autodiff.h"
#include "../statistics/statistics.h"
#include "../pseudorandom/montecarlo.h"
#include "../pseudorandom/sampling.h"

Go to the source code of this file.

Namespaces
namespace	theoretica
	Main namespace of the library which contains all functions and objects.
namespace	theoretica::stats
	Statistical functions.

Functions
template<typename Matrix = mat<real>, typename Dataset = vec<real>, enable_vector< Dataset > = true>
Matrix	theoretica::stats::covar_mat (const std::vector< Dataset > &v)
	Build the covariance matrix given a vector of datasets by computing the covariance between all couples of sets.
template<unsigned int N = 0, typename MultiDualFunction = autodiff::dreal_t<N>(*)(autodiff::dvec_t<N>)>
real	theoretica::stats::propagerr (MultiDualFunction f, const vec< real, N > &x_best, const vec< real, N > &delta_x)
	Automatically propagate uncertainties under quadrature on an arbitrary function given the uncertainties on the variables, the mean values of the variables and the function itself, by using automatic differentiation.
template<unsigned int N = 0, typename Matrix , enable_matrix< Matrix > = true, typename MultiDualFunction = autodiff::dreal_t<N>(*)(autodiff::dvec_t<N>)>
real	theoretica::stats::propagerr (MultiDualFunction f, const vec< real, N > &x_best, const Matrix &cm)
	Automatically propagate uncertainties under quadrature on an arbitrary function given the uncertainties on the variables, the mean values of the variables and the function itself, by using automatic differentiation.
template<unsigned int N = 0, typename MultiDualFunction = multidual<N>(*)(autodiff::dvec_t<N>), typename Dataset = vec<real, N>>
real	theoretica::stats::propagerr (MultiDualFunction f, const std::vector< Dataset > &v)
	Automatically propagate uncertainties under quadrature on an arbitrary function given the function and the set of measured data.
template<typename Function >
real	theoretica::stats::propagerr_mc (Function f, std::vector< pdf_sampler > &rv, unsigned int N=1E+6)
	Propagate the statistical error on a given function using the Monte Carlo method, by generating a sample following the probability distribution of the function and computing its standard deviation.

Detailed Description

Automatic propagation of uncertainties on arbitrary functions.