regress_model

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

Source code

General Methods

SMBcorr.regress_model(t_in, d_in, t_out, ORDER=2, CYCLES=[0.25, 0.5, 1.0, 2.0, 4.0, 5.0], RELATIVE=Ellipsis)[source]
Fits a synthetic signal to data over a time period by

ordinary or weighted least-squares

Parameters:
t_in: float

input time array

d_in: float

input 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]

list of 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