Short term work plan

[ocmadin]

• Improve model swap acceptance for the 'All' cases

In general, model swap acceptance ratios are lower for 'All' cases than they are for 'rhol+psat' cases. We should look at using better Q proposals, model mapping techniques, and swap frequencies to improve these ratios - they will probably be different for different compounds

• Run 10^7 step RJMC for all compounds in the 'rhol+Psat' case.

Currently completed:

• C2H6 (Bayes Factor = 2.8)
• N2 (Bayes Factor = 2.4)
• O2 (Bayes Factor = 8.0)

Todo:

• C2H2 (Good data coverage except for SurfTens, only coverage from 0.62Tc-0.7Tc)

• C2H4 (Good data coverage except for SurfTens, only coverage from 0.41Tc-0.65Tc)

• Br2 (Good data coverage except for SurfTens, only coverage from 0.47Tc-0.55Tc)

• Cl2 (Only Psat data available)

• C2F4 (Good data coverage except for SurfTens, No SurfTens data available)

• C2Cl4 (rhol and Psat data only from 0.4Tc-0.65Tc, no SurfTense data available)

• F2 (Good Psat data coverage, rhol only from 0.5Tc-0.6Tc, SurfTens only from 0.45Tc-0.55Tc)

• Run 10^7 step RJMC for selected compounds in the 'All' case

• Have completed simulations for C2H6, N2, but unsure if results are valid (100% model 0 sampling for N2, uncoverged distribution for C2H6)

• Will run for O2 in the near future

• Won't be possible to do this for Cl2,C2F4,C2Cl4

• Will be able to do with modified data ranges for C2H2,C2H4,Br2,F2

This is a relatively short term plan, after completing these tasks and looking at the distributions/Bayes factors, we can determine how to move forward. If there are things you think I am missing please let me know.

@ramess101

[ramess101]

This is a good start. A few ideas I would like to consider: 1) Toy problems where we generate data from: a) 3 parameter model with different degrees of scatter b) Conflicting data sets from different underlying parameter sets 2) Include the 1, 2 parameter models (simultaneous sampling/comparison of 4 models) 3) Include 3 parameter model where parameters are eps, sig, and Q 4) Sensitivity to error model, data ranges, amount of data, etc (could use toy problems for this)

…

On Monday, February 11, 2019, Owen Madin ***@***.***> wrote: - Improve model swap acceptance for the 'All' cases In general, model swap acceptance ratios are lower for 'All' cases than they are for 'rhol+psat' cases. We should look at using better Q proposals, model mapping techniques, and swap frequencies to improve these ratios - they will probably be different for different compounds - Run 10^7 step RJMC for all compounds in the 'rhol+Psat' case. Currently completed: - C2H6 (Bayes Factor = 2.8) - N2 (Bayes Factor = 2.4) - O2 (Bayes Factor = 8.0) Todo: - C2H2 (Good data coverage except for SurfTens, only coverage from 0.62Tc-0.7Tc) - C2H4 (Good data coverage except for SurfTens, only coverage from 0.41Tc-0.65Tc) - Br2 (Good data coverage except for SurfTens, only coverage from 0.47Tc-0.55Tc) - Cl2 (Only Psat data available) - C2F4 (Good data coverage except for SurfTens, No SurfTens data available) - C2Cl4 (rhol and Psat data only from 0.4Tc-0.65Tc, no SurfTense data available) - F2 (Good Psat data coverage, rhol only from 0.5Tc-0.6Tc, SurfTens only from 0.45Tc-0.55Tc) - Run 10^7 step RJMC for selected compounds in the 'All' case - Have completed simulations for C2H6, N2, but unsure if results are valid (100% model 0 sampling for N2, uncoverged distribution for C2H6) - Will run for O2 in the near future - Won't be possible to do this for Cl2,C2F4,C2Cl4 - Will be able to do with modified data ranges for C2H2,C2H4,Br2,F2 This is a relatively short term plan, after completing these tasks and looking at the distributions/Bayes factors, we can determine how to move forward. If there are things you think I am missing please let me know. @ramess101 <https://github.com/ramess101> — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#5>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AWUvhDXtOhxeILBkSc85-jOwJ-FAFYjFks5vMgAggaJpZM4a1Sop> .