1 sigma error estimation by maximum likelihood approach
In this MR, the function structure of Maximum Likelihood Estimation (MLE) is similar with MCMC function in measurement.py
.
_MLE
in ProcessMeasurement
class is base function of MLE.
With this, run_mle
in ProcessSensingMeasurement
, and ProcessActuationMeasurement
respectively call this function to run MLE.
The help function for MLE are also created here, _MLE_ln_prob
and _MLE_log_norm_pdf
to compute log-likelihood for MLE.
The Likelihood_ratio
is function to help calculation and provide a way to get upper and lower (+/-) sigma value of fitting parameters
In example directory, I put example_mle.py
to perform how to use this method function.
Edited by Hsiang-Yu Huang