(Difference between revisions)
 Revision as of 21:47, 16 March 2022Werner (Talk | contribs)← Previous diff Revision as of 21:58, 16 March 2022Werner (Talk | contribs) Next diff → Line 71: Line 71: Here is the program [[TemperingConductance.py| TemperingConductance.py]] which iterates over the powerset of Omega, in order to compute the conductance of the Simulated Tempering problem. Here is the program [[TemperingConductance.py| TemperingConductance.py]] which iterates over the powerset of Omega, in order to compute the conductance of the Simulated Tempering problem. + + Here is the program [[TVDTemperingLift.py| TVDTemperingLift.py]] which computes the probability distribution pi^t and the TVD with the stationary probability distribution.

## Revision as of 21:58, 16 March 2022

This is the homepage of my 2022 lecture course on Advanced topics in Markov-chain Monte Carlo

Here is the CM1.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM2.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM3.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM4.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM5.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM6.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM7.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the CM8.1 of my 2022 lecture course Advanced topics in Markov-chain Monte Carlo.

Here is the program TemperingConductance.py which iterates over the powerset of Omega, in order to compute the conductance of the Simulated Tempering problem.

Here is the program TVDTemperingLift.py which computes the probability distribution pi^t and the TVD with the stationary probability distribution.