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Could you point to a resource that explains method well?
by Bootvis 5y ago
Could you point to a resource that explains method well?
- kqr 5y agoUnfortunately my only exposure to this is a University course I took called Computer Intensive Methods in Mathematical Statistics[1]. It was a really good course, but at the time I was not in a mental space where I could get the most out of it, so I'm kind of hoping someone else can point to a solid textbook or something. [1]: https://www.kth.se/student/kurser/kurs/SF2955?l=en https://www.kth.se/student/kurser/kurs/SF2955?l=en
- nbernard 5y agoI liked the book "Statistical Mechanics: Algorithms and Computations" by Werner Krauth. It's oriented toward physics, but IIRC he links Monte Carlo simulations to the path integral formalism. There is also a MOOC (same title, same author) on Coursera that I found interesting. It doesn't not go to the same depth as the book however. They are more complementing each other, the book for theory, the MOOC for implementation exercises.
- sitkack 5y agothis looks wonderful https://www.coursera.org/learn/statistical-mechanics https://www.coursera.org/learn/statistical-mechanics
- oyoman 5y agoI don't know if I can plug-in here some of the materials I prepared some years ago. It might help to bridge/connect the use of Monte Carlo techniques and its relations with integration: https://github.com/ChristopheRappold/MCandPython/blob/master/session2.ipynb https://github.com/ChristopheRappold/MCandPython/blob/master... Also just to mention something else that is very interesting related with MC : "quasi-Monte Carlo techniques" (small example in https://github.com/ChristopheRappold/MCandPython/blob/master/session3.ipynb https://github.com/ChristopheRappold/MCandPython/blob/master... ). For people interested in MC, just take a look to those keywords.