Journal of the American Statistical Association · 1995 · 72 citations · 0 references
Natural SciencesMathematicsProbability TheoryStatistical ModelingStatisticsBayesian ComputationBayesian InferenceBayesian ModelingBayesian StatisticsMarkov Chain Monte CarloStatistical InferenceBayesian EstimationBayesian Markov Chain Monte CarloMarkov Chain Monte Carlo InferenceMarkov Chain Monte Carlo Posterior SamplingMathematical RepresentationPosterior Distribution Of ParametersPosterior EstimationStable Distributions
Very little work on stable distribution parameter estimation and inference appears in the literature due to the nonexistence of the probability density function. This has led in particular to a dearth of Bayesian work in this area. But Bayesian computation via Markov chain Monte Carlo allows us to sample from the distribution of the parameters of the stable distributions, by exploiting a particular mathematical representation involving the stable density.