tlx

Calculate the regression polynomial \( a_0+a_1x^1+a_2x^2+\cdots+a_nx^n \) from a list of 2D points. More...
#include <polynomial_regression.hpp>
Classes  
struct  Coefficients 
polynomial stored as the coefficients of \( a_0+a_1 x^1+a_2 x^2+\cdots+a_n x^n \) More...  
struct  Point 
2D point More...  
Public Member Functions  
PolynomialRegression (size_t order)  
start new polynomial regression calculation More...  
size_t  size () const 
number of points More...  
PolynomialRegression &  add (const Type &x, const Type &y) 
add point. this invalidates cached coefficients until next evaluate() More...  
const Point &  point (size_t i) 
return a point. Only available if WithStore is true. More...  
Type  r_square () 
get r^2. Only available if WithStore is true. More...  
Type  evaluate (const Type &x) 
returns value of y predicted by the polynomial for a given value of x More...  
const Coefficients &  coefficients () 
return coefficients vector More...  
Protected Member Functions  
void  fit_coefficients () 
polynomial regression by inverting a Vandermonde matrix. More...  
Protected Attributes  
size_t  order_ 
polynomial order More...  
std::vector< Point >  points_ 
list of stored points if WithStore, else empty. More...  
size_t  size_ 
number of points added More...  
std::vector< Type >  X_ 
X_ = vector that stores values of sigma(x_i^2n) More...  
std::vector< Type >  Y_ 
Y_ = vector to store values of sigma(x_i^order * y_i) More...  
Coefficients  coefficients_ 
cached coefficients More...  
Calculate the regression polynomial \( a_0+a_1x^1+a_2x^2+\cdots+a_nx^n \) from a list of 2D points.
See also https://en.wikipedia.org/wiki/Polynomial_regression
If WithStore is false, then the sums are aggregated directly such that the class retains O(1) size independent of the number of points. if WithStore is true then the points are stored in a vector and can be retrieved.
Definition at line 33 of file polynomial_regression.hpp.

inline 
start new polynomial regression calculation
Definition at line 37 of file polynomial_regression.hpp.

inline 
add point. this invalidates cached coefficients until next evaluate()
Definition at line 52 of file polynomial_regression.hpp.

inline 
return coefficients vector
Definition at line 127 of file polynomial_regression.hpp.

inline 
returns value of y predicted by the polynomial for a given value of x
Definition at line 122 of file polynomial_regression.hpp.

inlineprotected 
polynomial regression by inverting a Vandermonde matrix.
Definition at line 154 of file polynomial_regression.hpp.

inline 
return a point. Only available if WithStore is true.
Definition at line 78 of file polynomial_regression.hpp.

inline 
get r^2. Only available if WithStore is true.
mean value of y
Definition at line 96 of file polynomial_regression.hpp.

inline 
number of points
Definition at line 42 of file polynomial_regression.hpp.

protected 
cached coefficients
Definition at line 151 of file polynomial_regression.hpp.

protected 
polynomial order
Definition at line 136 of file polynomial_regression.hpp.

protected 
list of stored points if WithStore, else empty.
Definition at line 139 of file polynomial_regression.hpp.

protected 
number of points added
Definition at line 142 of file polynomial_regression.hpp.

protected 
X_ = vector that stores values of sigma(x_i^2n)
Definition at line 145 of file polynomial_regression.hpp.

protected 
Y_ = vector to store values of sigma(x_i^order * y_i)
Definition at line 148 of file polynomial_regression.hpp.