Parameter estimation for complex physical problems often suffers from finding ‘solutions’ that are not physically realistic. The PEUQSE software provides tools for finding physically realistic parameter estimates, graphs of the parameter estimate positions within parameter space, and plots of the final simulation results.
The below is not accurate anymore. It probably should also be converted partially into a bulleted list.
THe readme should also more strongly point to the rtf file and also the UserInputPossibilities.py file
PEUQSE has four types of posterior distribution sampling options as of Oct 2020. Two Markov Chain Monte Carlo sampling options: EnsembleSliceSampling and MetropolisHastings; and two even distribution (unbiased and unguided) sampling options: multistart grid sampling and multistart uniform distribution sampling. These are compared a little bit in Example00 in the examples. The latter two sampling types are rarely included in other packages but can be very important for scientific applications and for rough response surfaces. It is often important to know whether the solution found is a unique solution, and the unbiased and unguided sampling can be used for verification of the uniqueness of a solution.
There is a logfile generated called mcmc_log_file.txt or permutations_log_file.txt (along with other files in the directory). You will also get the following plots, some of which can be further customized, such as removing the bars from the contour plots. These plots automatically generated by PEUQSE:
The below is not accurate anymore. It probably should also be converted partially into a bulleted list.
THe readme should also more strongly point to the rtf file and also the UserInputPossibilities.py file
PEUQSE has four types of posterior distribution sampling options as of Oct 2020. Two Markov Chain Monte Carlo sampling options: EnsembleSliceSampling and MetropolisHastings; and two even distribution (unbiased and unguided) sampling options: multistart grid sampling and multistart uniform distribution sampling. These are compared a little bit in Example00 in the examples. The latter two sampling types are rarely included in other packages but can be very important for scientific applications and for rough response surfaces. It is often important to know whether the solution found is a unique solution, and the unbiased and unguided sampling can be used for verification of the uniqueness of a solution.
There is a logfile generated called mcmc_log_file.txt or permutations_log_file.txt (along with other files in the directory). You will also get the following plots, some of which can be further customized, such as removing the bars from the contour plots. These plots automatically generated by PEUQSE: