PINE LIBRARY
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.
Biblioteca do Pine
In true TradingView spirit, the author has published this Pine code as an open-source library so that other Pine programmers from our community can reuse it. Cheers to the author! You may use this library privately or in other open-source publications, but reuse of this code in publications is governed by House Rules.
Aviso legal
As informações e publicações não devem ser e não constituem conselhos ou recomendações financeiras, de investimento, de negociação ou de qualquer outro tipo, fornecidas ou endossadas pela TradingView. Leia mais em Termos de uso.
Biblioteca do Pine
In true TradingView spirit, the author has published this Pine code as an open-source library so that other Pine programmers from our community can reuse it. Cheers to the author! You may use this library privately or in other open-source publications, but reuse of this code in publications is governed by House Rules.
Aviso legal
As informações e publicações não devem ser e não constituem conselhos ou recomendações financeiras, de investimento, de negociação ou de qualquer outro tipo, fornecidas ou endossadas pela TradingView. Leia mais em Termos de uso.