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Gibbs sampling

Known as: Blocked Gibbs sampling, Gibbs sampler, Gibbs 
In statistics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are… 
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Related topics

Related topics

49 relations
AlgorithmAutocorrelationBayesian inference using Gibbs samplingBayesian network

Broader (1)

Markov chain Monte Carlo

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Risk-Based Sensor Placement for Contaminant Detection in Water Distribution Systems
A method for optimizing sensor locations to effectively and efficiently detect contamination in a water distribution network is… 
Highly Cited
2007
Highly Cited
2007
Arthropod community diversity and trophic structure: a comparison between extremes of plant stress
Abstract 1. Previous studies have shown that plant stress and plant vigour impact the preference and performance of many insect… 
Highly Cited
2006
Highly Cited
2006
A Sampling-Based Approach to Optimizing Top-k Queries in Sensor Networks
Wireless sensor networks generate a vast amount of data. This data, however, must be sparingly extracted to conserve energy… 
Highly Cited
2005
Highly Cited
2005
Hybrid PRM Sampling with a Cost-Sensitive Adaptive Strategy
A number of advanced sampling strategies have been proposed in recent years to address the narrow passage problem for… 
Highly Cited
2000
Highly Cited
2000
A Practical Handbook of Speech Coders
INTRODUCTION SPEECH PRODUCTION The Speech Chain Articulation Source-Filter Model SPEECH ANALYSIS TECHNIQUES Sampling and the… 
Highly Cited
1999
Highly Cited
1999
Ranked set sampling for ecological research: accounting for the total costs of sampling
Researchers aim to design environmental studies that optimize precision and allow for generalization of results, while keeping… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1993
Highly Cited
1993
Sampling Methods for Multiresource Forest Inventory
Focus, Fundamental Concepts, and Theory. Probabilistic Sampling Strategies. Forest Sampling--Single Level. Multi-Information… 
Highly Cited
1979
Highly Cited
1979
A comparasion of three resequencing algorithms for the reduction of matrix profile and wavefront
Three widely-used nodal resequencing algorithms were tested and compared for their ability to reduce matrix profile and root-mean… 
Highly Cited
1977
Highly Cited
1977
Methods of Air Sampling and Analysis
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