Results 131 to 140 of about 50,759 (165)
Some of the next articles are maybe not open access.
2004
We maintain that the analysis and synthesis of random fields is much faster in a hierarchical setting. In particular, complicated long-range interactions at a fine scale become progressively more local (and therefore more efficient) at coarser levels. The key to effective coarse-scale activity is the proper model definition at those scales. This can be
openaire +2 more sources
We maintain that the analysis and synthesis of random fields is much faster in a hierarchical setting. In particular, complicated long-range interactions at a fine scale become progressively more local (and therefore more efficient) at coarser levels. The key to effective coarse-scale activity is the proper model definition at those scales. This can be
openaire +2 more sources
2003
Markov chain Monte Carlo (MCMC) algorithms are now widely used in virtually all areas of statistics. In particular, spatial applications featured very prominently in the early development of the methodology (Geman & Geman 1984), and they still provide some of the most challenging problems for MCMC techniques.
Petros Dellaportas, Gareth O. Roberts
openaire +1 more source
Markov chain Monte Carlo (MCMC) algorithms are now widely used in virtually all areas of statistics. In particular, spatial applications featured very prominently in the early development of the methodology (Geman & Geman 1984), and they still provide some of the most challenging problems for MCMC techniques.
Petros Dellaportas, Gareth O. Roberts
openaire +1 more source
MCMC algorithms for Subset Simulation
Probabilistic Engineering Mechanics, 2015Iason Papaioannou +2 more
exaly
Bayesian MCMC flood frequency analysis with historical information
Journal of Hydrology, 2005Jery R. Stedinger +1 more
exaly