Code for performing the weighted Least Squares Including Correlation in Error (WLS-ICE) algorithm when fitting a function to ensemble averages, implemented in languages listed below, with example data with M=100 fractional Brownian motion trajectories (generated with parameters as in paper "Fitting a function to time-dependent ensemble averaged data") (or arXiv):
-
Python scripts that read in the data and apply the WLS-ICE algorithm to it. Run ./example.py ../data from python-folder, for a demonstration.
-
Octave/Matlab - code ported from Python.
f.m
,df.m
, andd2f.m
defines the analytical function to fit, its gradient and hessian, respectively. Runexample.m
file for example. -
Hy Lisp, analogous to Python.
We also provide the scripts (Python) used to generate trajectories for the four example systems.
All code is made available under GNU General Public License v3. https://www.gnu.org/licenses/gpl-3.0.html