| libcmaes 0.10.2
    A C++11 library for stochastic optimization with CMA-ES | 
profile likelihood object holder as a set of points and values. More...
#include <libcmaes/pli.h>
| Public Member Functions | |
| pli (const int &k, const int &samplesize, const int &dim, const dVec &xm, const double &fvalue, const double &fup, const double &delta) | |
| profile likelihood constructor | |
| std::pair< double, double > | getMinMax (const double &fvalue, int &minindex, int &maxindex) | 
| find bounds around the objective function parameters for a given value of f, base on pre-computed profile likelihood points. | |
| void | setMinMax () | 
| void | setErrMinMax () | 
| sets the errors bounds for this profile likelihood. | |
| double | get_err_min () const | 
| get lower error bound | |
| double | get_err_max () const | 
| get upper error bound | |
| int | get_k () const | 
| int | get_samplesize () const | 
| dVec | get_fvaluem () const | 
| dMat | get_xm () const | 
| double | get_min () const | 
| double | get_max () const | 
| Private Attributes | |
| int | _k = -1 | 
| int | _samplesize = 0 | 
| dVec | _fvaluem | 
| dMat | _xm | 
| double | _min = 0.0 | 
| double | _max = 0.0 | 
| double | _errmin = 0.0 | 
| double | _errmax = 0.0 | 
| int | _minindex = -1 | 
| int | _maxindex = -1 | 
| std::vector< int > | _err | 
| double | _fup | 
| double | _delta | 
| Friends | |
| class | CMASolutions | 
| template<class U > | |
| class | errstats | 
profile likelihood object holder as a set of points and values.
| 
 | inline | 
profile likelihood constructor
| k | dimension in which the profile likelihood was computed | 
| samplesize | number of steps of the linesearch direction | 
| dim | dimension of the objective function parameter space | 
| xm | vector of parameters at fvalue | 
| fvalue | the function minima around which the profile likelihood was computed | 
| fup | the function deviation for which the profile likelihood was computed | 
| delta | tolerance around fvalue + fup for which the profile likelihood was computed | 
| 
 | inline | 
get upper error bound
| 
 | inline | 
get lower error bound
| 
 | inline | 
find bounds around the objective function parameters for a given value of f, base on pre-computed profile likelihood points.
| fvalue | function value | 
| minindex | index of the profile likelihood point that is the lower bound | 
| maxindex | index of the profile likelihood point that is the upper bound | 
| 
 | inline | 
\brie sets the bounds for this profile likelihood object based on original function value + fup