Library "regressions" This library computes least square regression models for polynomials of any form for a given data set of x and y values. fit(X, y, reg_type, degrees) Takes a list of X and y values and the degrees of the polynomial and returns a least square regression for the given polynomial on the dataset. Parameters: X (array) : (float ) ...
Linear Time-Invariant (LTI) filters are fundamental tools in signal processing that operate with consistent behavior over time and linearly respond to input signals. They are crucial for analyzing and manipulating signals in various applications, ensuring the output signal's integrity is maintained regardless of when an input is applied or its magnitude. The...
Library "regress" produces the slope (beta), y-intercept (alpha) and coefficient of determination for a linear regression regress(x, y, len) regress: computes alpha, beta, and r^2 for a linear regression of y on x Parameters: x : the explaining (independent) variable y : the dependent variable len : use the most recent "len" values of x and...