Stick-breaking representation and computation for normalized generalized gamma processes
From MaRDI portal
Publication:746052
DOI10.1007/s13171-015-0070-yzbMath1322.62108OpenAlexW2212262128MaRDI QIDQ746052
Publication date: 15 October 2015
Published in: Sankhyā. Series A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13171-015-0070-y
Bayesian nonparametricsnormalized generalized gamma processstick-breaking representationgamma titled stable random variable
Density estimation (62G07) Bayesian inference (62F15) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A note on generating random variables with log-concave densities
- On a class of Bayesian nonparametric estimates: I. Density estimates
- Statistical properties of the generalized inverse Gaussian distribution
- Size-biased sampling of Poisson point processes and excursions
- Exact mean integrated squared error
- Modelling heterogeneity in survival analysis by the compound Poisson distribution
- The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator
- Distributional results for means of normalized random measures with independent increments
- Prior distributions on spaces of probability measures
- Combinatorial stochastic processes. Ecole d'Eté de Probabilités de Saint-Flour XXXII -- 2002.
- Bayesian nonparametric analysis for a generalized Dirichlet process prior
- A Bayesian analysis of some nonparametric problems
- Bayesian Poisson process partition calculus with an application to Bayesian Lévy moving averages
- On the stick-breaking representation of normalized inverse Gaussian priors
- Posterior Analysis for Normalized Random Measures with Independent Increments
- Survival models for heterogeneous populations derived from stable distributions
- The Simulation of Generalized Inverse Gaussian and Hyperbolic Random Variables
- Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models
- Random variate generation for exponentially and polynomially tilted stable distributions
- Sampling Exponentially Tilted Stable Distributions
- Gibbs Sampling Methods for Stick-Breaking Priors
- Exercises in Probability
- Generalized Gamma measures and shot-noise Cox processes
- Controlling the Reinforcement in Bayesian Non-Parametric Mixture Models
- Random Fragmentation and Coagulation Processes
- Concepts of Independence for Proportions with a Generalization of the Dirichlet Distribution
- A Representation of Independent Increment Processes without Gaussian Components
- Modeling with normalized random measure mixture models
- MCMC for normalized random measure mixture models
