Results 31 to 40 of about 2,583,540 (350)
Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy [PDF]
, 2017 Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science.
Sanjib Sharma
semanticscholar +1 more source
Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau [PDF]
SIAM Journal of Imaging Sciences, 2016 Modern imaging methods rely strongly on Bayesian inference techniques to solve challenging imaging problems. Currently, the predominant Bayesian computation approach is convex optimization, which scales very efficiently to high-dimensional image models ...
Alain Durmus, É. Moulines, M. Pereyra
semanticscholar +1 more source
Data Analysis Recipes: Using Markov Chain Monte Carlo [PDF]
, 2017 Markov Chain Monte Carlo (MCMC) methods for sampling probability density functions (combined with abundant computational resources) have transformed the sciences, especially in performing probabilistic inferences, or fitting models to data.
D. Hogg, D. Foreman-Mackey
semanticscholar +1 more source
Theoretical Computer Science, 2011 AbstractNotions of specification, implementation, satisfaction, and refinement, together with operators supporting stepwise design, constitute a specification theory. We construct such a theory for Markov Chains (MCs) employing a new abstraction of a Constraint MC.
Caillaud, Benoit +5 more
openaire +7 more sources
Average-Based Fuzzy Time Series Markov Chain Based on Frequency Density Partitioning
Journal of Applied Mathematics, 2023 Fuzzy time series (FTS) is one of the forecasting methods that has been developed until now. The fuzzy time series is a forecasting method that uses the concept of fuzzy logic, which Song and Chissom first introduced.
Susilo Hariyanto +3 more
doaj +1 more source
Polynomial Recurrence of Time-inhomogeneous Markov Chains
Austrian Journal of Statistics, 2023 This paper is devoted to establishing conditions that guarantee the existence of a p-th moment of the time it takes for a timeinhomogeneous Markov chain to hit some set C.
Vitaliy Golomoziy, Olha Moskanova
doaj +1 more source
Prediksi Kurs Rupiah Terhadap Dolar Dengan FTS-Markov Chain Dan Hidden Markov Model
Jurnal Derivat, 2019 Hidden Markov model is a development of the Markov chain where the state cannot be observed directly (hidden), but can only be observed, a set of other observations and combination of fuzzy logic and Markov chain to predict Rupiah exchange rate against ...
Maria Titah Jatipaningrum +2 more
doaj +1 more source
Assessing significance in a Markov chain without mixing [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2016 Significance Markov chains are simple mathematical objects that can be used to generate random samples from a probability space by taking a random walk on elements of the space. Unfortunately, in applications, it is often unknown how long a chain must be
M. Chikina, A. Frieze, W. Pegden
semanticscholar +1 more source
Singles in a Markov chain [PDF]
Publications de l'Institut Mathematique, 2008 Let {Xi, i _? 1} denote a sequence of variables that take values in {0, 1} and suppose that the sequence forms a Markov chain with transition matrix P and with initial distribution (q, p) = (P(X1 = 0), P(X1 = 1)). Several authors have studied the quantities Sn, Y (r) and AR(n), where Sn = ?n i=1 Xi denotes the number of successes, where Y (r) denotes ...
Omey, Edward, Van Gulck, Stefan
openaire +4 more sources