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.
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Biblioteca do Pine
Em verdadeiro espírito TradingView, o autor publicou este código Pine como uma biblioteca de código aberto para que outros programadores Pine da nossa comunidade possam reutilizá-lo. Parabéns ao autor! Você pode usar esta biblioteca de forma privada ou em outras publicações de código aberto, mas a reutilização deste código em publicações é regida pelas Regras da Casa.
Aviso legal
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.