regress

  • Estimates a modeled time series for extrapolation by least-squares regression

Source code

General Methods

FirnCorr.regress(t_in: ndarray, d_in: ndarray, t_out: ndarray, order: int = 2, cycles: list[float] = [0.25, 0.5, 1.0, 2.0, 4.0, 5.0], relative: float = Ellipsis)[source]
Fits a synthetic signal to data over a time period by

ordinary or weighted least-squares

Parameters:
t_in: float

Time array

d_in: float

Data array

order: int, default 2

Maximum polynomial order in fit

  • 0: constant

  • 1: linear

  • 2: quadratic

cycles: list, default [0.25,0.5,1.0,2.0,4.0,5.0]

Cyclical terms

relative: float or List, default Ellipsis

Epoch for calculating relative dates

  • float: use exact value as epoch

  • list: use mean from indices of available times

  • Ellipsis: use mean of all available times

Returns:
d_out: float

Reconstructed time series