FunctionPolynomialFit

Library "FunctionPolynomialFit"
Performs Polynomial Regression fit to data.
In statistics, polynomial regression is a form of regression analysis in which
the relationship between the independent variable x and the dependent variable
y is modelled as an nth degree polynomial in x.
reference:
en.wikipedia.org/wiki/Polynomial_regression
bragitoff.com/2018/06/polynomial-fitting-c-program/
gauss_elimination(A, m, n) Perform Gauss-Elimination and returns the Upper triangular matrix and solution of equations.
Parameters:
A: float matrix, data samples.
m: int, defval=na, number of rows.
n: int, defval=na, number of columns.
Returns: float array with coefficients.
polyfit(X, Y, degree) Fits a polynomial of a degree to (x, y) points.
Parameters:
X: float array, data sample x point.
Y: float array, data sample y point.
degree: int, defval=2, degree of the polynomial.
Returns: float array with coefficients.
note:
p(x) = p[0] * x**deg + ... + p[deg]
interpolate(coeffs, x) interpolate the y position at the provided x.
Parameters:
coeffs: float array, coefficients of the polynomial.
x: float, position x to estimate y.
Returns: float.
Performs Polynomial Regression fit to data.
In statistics, polynomial regression is a form of regression analysis in which
the relationship between the independent variable x and the dependent variable
y is modelled as an nth degree polynomial in x.
reference:
en.wikipedia.org/wiki/Polynomial_regression
bragitoff.com/2018/06/polynomial-fitting-c-program/
gauss_elimination(A, m, n) Perform Gauss-Elimination and returns the Upper triangular matrix and solution of equations.
Parameters:
A: float matrix, data samples.
m: int, defval=na, number of rows.
n: int, defval=na, number of columns.
Returns: float array with coefficients.
polyfit(X, Y, degree) Fits a polynomial of a degree to (x, y) points.
Parameters:
X: float array, data sample x point.
Y: float array, data sample y point.
degree: int, defval=2, degree of the polynomial.
Returns: float array with coefficients.
note:
p(x) = p[0] * x**deg + ... + p[deg]
interpolate(coeffs, x) interpolate the y position at the provided x.
Parameters:
coeffs: float array, coefficients of the polynomial.
x: float, position x to estimate y.
Returns: float.
Penafian
Maklumat dan penerbitan adalah tidak bertujuan, dan tidak membentuk, nasihat atau cadangan kewangan, pelaburan, dagangan atau jenis lain yang diberikan atau disahkan oleh TradingView. Baca lebih dalam Terma Penggunaan.
Penafian
Maklumat dan penerbitan adalah tidak bertujuan, dan tidak membentuk, nasihat atau cadangan kewangan, pelaburan, dagangan atau jenis lain yang diberikan atau disahkan oleh TradingView. Baca lebih dalam Terma Penggunaan.