Results 31 to 40 of about 2,455,160 (79)

Quantifying the uncertainty in change points [PDF]

, 2011
Quantifying the uncertainty in the location and nature of change points in time series is important in a variety of applications. Many existing methods for estimation of the number and location of change points fail to capture fully or explicitly the ...
Aston, John A. D., Christopher F. H. Nam, John A. D. Aston, Johansen, Adam M., Nam, Christopher F. H., Adam M. Johansen   +5 more
core   +1 more source

Markov chain Monte Carlo methods for state-space models with point process observations [PDF]

, 2012
This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan, Girolami, Mark, Yuan, Ke   +2 more
core   +1 more source

Speculative moves : multithreading Markov Chain Monte Carlo programs [PDF]

, 2008
The increasing availability of multi-core and multi-processor architectures provides new opportunities for improving the performance of many computer simulations.
Bhalerao, Abhir, Byrd, Jonathan M. R., Jarvis, Stephen A.   +2 more
core   +1 more source

Quasi-exact Approximation of Hidden Markov Chain Filters [PDF]

This paper studies the application of exact simulation methods for multi-dimensional multiplicative noise stochastic differential equations to filtering.
Eckhard Platen, Renata Rendek
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Implied distributions in multiple change point problems [PDF]

, 2011
A method for efficiently calculating exact marginal, conditional and joint distributions for change points defined by general finite state Hidden Markov Models is proposed.
Aston, John A. D., D. E. K. Martin, Peng, Jyh-Ying, Martin, D. E. K., J. A. D. Aston, J. Y. Peng   +5 more
core   +1 more source

Conditioning an additive functional of a markov chain to stay non-negative. I, Survival for a long time [PDF]

, 2005
Let (X-t)(t >= 0) be a continuous-time irreducible Markov chain on a finite state space E, let v be a map v: E -> R \ {0}, and let (phi(t))(t >= 0) be an additive functional defined by phi(t) = integral(0)(t)(X-s) ds.
Warren, Jon, Lazic, Zorana, Jacka, Saul D.   +2 more
core   +1 more source

Uniform bounds on the 1-norm of the inverse of lower triangular Toeplitz matrices [PDF]

, 2011
A uniform bound on the 1-norm is given for the inverse of a lower triangular Toeplitz matrix with non-negative monotonically decreasing entries whose limit is zero. The new bound is sharp under certain specified constraints.
J.Y. Yuan, S. McKee, Yuan, Y.X., Liu, X., X. Liu, McKee, S., Yuan, J.Y., Y.X. Yuan   +7 more
core   +2 more sources

On the containment condition for adaptive Markov Chain Monte Carlo algorithms [PDF]

, 2009
This paper considers ergodicity properties of certain adaptive Markov chain Monte Carlo (MCMC) algorithms for multidimensional target distributions, in particular Adaptive Metropolis and Adaptive Metropolis-within-Gibbs.
Rosenthal, Jeffrey S. (Jeffrey Seth), Bai, Yan, Roberts, Gareth O.   +2 more
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apotschka/markov-chain-scenario-trees: First release

, 2019
<p>This is the first release of Markov chain scenario trees.</p> <p>Contents:</p> <ul> <li>A polynomial-time algorithm to generate optimally pruned Markov chain scenario trees</li> <li>Functions for ...
Andreas Potschka, Andreas Potschka (7111493)   +1 more
core   +1 more source

Markov Chain Monte Carlo Technology [PDF]

In the past fifteen years computational statistics has been enriched by a powerful, somewhat abstract method of generating variates from a target probability distribution that is based on Markov chains whose stationary distribution is the probability ...
Chib, Siddhartha
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