Information gains from Monte Carlo Markov Chains
نویسندگان
چکیده
منابع مشابه
Ordering Monte Carlo Markov Chains
Markov chains having the same stationary distribution can be partially ordered by performance in the central limit theorem. We say that one chain is at least as good as another in the e ciency partial ordering if the variance in the central limit theorem is at least as small for every L( ) functional of the chain. Peskun partial ordering implies e ciency partial ordering [25, 30]. Here we show ...
متن کاملLecture 18: Monte Carlo and Markov Chains
For Halloween, we come as a math course 1 Monte Carlo Integration Suppose we want to evaluate a definite integral,
متن کاملLecture 18: Monte Carlo and Markov Chains
For Halloween, we come as a math course 1 Monte Carlo Integration Suppose we want to evaluate a definite integral,
متن کاملLecture 18: Monte Carlo and Markov Chains
For Halloween, we come as a math course 1 Monte Carlo Integration Suppose we want to evaluate a definite integral,
متن کاملPutting Markov Chains Back into Markov Chain Monte Carlo
Markov chain theory plays an important role in statistical inference both in the formulation of models for data and in the construction of efficient algorithms for inference. The use of Markov chains in modeling data has a long history, however the use of Markov chain theory in developing algorithms for statistical inference has only become popular recently. Using mark-recapture models as an il...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The European Physical Journal Plus
سال: 2020
ISSN: 2190-5444
DOI: 10.1140/epjp/s13360-020-00390-z