Statistics – Methodology
Scientific paper
2011-04-11
Statistical Science 2010, Vol. 25, No. 4, 429-449
Statistics
Methodology
Published in at http://dx.doi.org/10.1214/09-STS309 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M
Scientific paper
10.1214/09-STS309
In recent years, a variety of extensions and refinements have been developed for data augmentation based model fitting routines. These developments aim to extend the application, improve the speed and/or simplify the implementation of data augmentation methods, such as the deterministic EM algorithm for mode finding and stochastic Gibbs sampler and other auxiliary-variable based methods for posterior sampling. In this overview article we graphically illustrate and compare a number of these extensions, all of which aim to maintain the simplicity and computation stability of their predecessors. We particularly emphasize the usefulness of identifying similarities between the deterministic and stochastic counterparts as we seek more efficient computational strategies. We also demonstrate the applicability of data augmentation methods for handling complex models with highly hierarchical structure, using a high-energy high-resolution spectral imaging model for data from satellite telescopes, such as the Chandra X-ray Observatory.
Meng Xiao-Li
van Dyk David A.
No associations
LandOfFree
Cross-Fertilizing Strategies for Better EM Mountain Climbing and DA Field Exploration: A Graphical Guide Book does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Cross-Fertilizing Strategies for Better EM Mountain Climbing and DA Field Exploration: A Graphical Guide Book, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cross-Fertilizing Strategies for Better EM Mountain Climbing and DA Field Exploration: A Graphical Guide Book will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-58428