Monte Carlo Bootstrap
The main work of Monte Carlo is to "Get some confidence estimates".
The Monte Carlo plugin is used to obtain estimates of the confidence limits for a model’s parameters. This is in the context where experimental data exists and a parameter minimization method, such as Levenberg-Marquardt or Nelder-Mead has already been used in order to find a parameter minimum.
The Monte Carlo algorithm is used subsequently at this minimum and will give an estimate of parameter confidence limits corresponding to the variance in the original experimental data.
The plugin has properties such as the size of the Monte Carlo population, minimization algorithm to use (e.g. Nelder-Mead or Levenberg-Marquardt), and on output, confidence limits for each involved parameter.
With some past updates, Monte Carlo is not working mainly due to the modifications in rrplugins and change of python version from 2.x to 3.x. I have modified the wrapper to let it work. Majorly the problem was with the passing of variables from Python to C.
Link to the sample code: https://github.com/debashish05/Sample-scripts-to-run-plugins-in-RRplugins-/blob/master/monte_carlo_bsExample.py
Output graph:
The mean value of the parameter comes out to be k1= 1.1499498230224052.
Comments
Post a Comment