@InProceedings{7362776,
  author = {A. Baussard and J. Tourneret},
  booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},
  title = {Bayesian parameter estimation for asymmetric power distributions},
  year = {2015},
  pages = {2206-2210},
  abstract = {This paper proposes a hierarchical Bayesian model for estimating the parameters of asymmetric power distributions (APDs). These distributions are defined by shape, scale and asymmetry parameters which make them very flexible for approximating empirical distributions. A hybrid Markov chain Monte Carlo method is then studied to sample the unknown parameters of APDs. The generated samples can be used to compute the Bayesian estimators of the unknown APD parameters. Numerical experiments show the good performance of the proposed estimation method. An application to an image segmentation problem is finally investigated.},
  keywords = {image segmentation;Markov processes;Monte Carlo methods;parameter estimation;Bayesian parameter estimation;asymmetric power distributions;APD parameter;hybrid Markov chain Monte Carlo method;image segmentation;Bayes methods;Image segmentation;Shape;Markov processes;Histograms;Estimation;Europe;Asymmetric power distributions;hierarchical Bayesian model;MCMC;Gibbs sampler;Image segmentation},
  doi = {10.1109/EUSIPCO.2015.7362776},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570102961.pdf},
}

{"_id":"8sbhm2pzbEMDdLP68","bibbaseid":"baussard-tourneret-bayesianparameterestimationforasymmetricpowerdistributions-2015","authorIDs":[],"author_short":["Baussard, A.","Tourneret, J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["A."],"propositions":[],"lastnames":["Baussard"],"suffixes":[]},{"firstnames":["J."],"propositions":[],"lastnames":["Tourneret"],"suffixes":[]}],"booktitle":"2015 23rd European Signal Processing Conference (EUSIPCO)","title":"Bayesian parameter estimation for asymmetric power distributions","year":"2015","pages":"2206-2210","abstract":"This paper proposes a hierarchical Bayesian model for estimating the parameters of asymmetric power distributions (APDs). These distributions are defined by shape, scale and asymmetry parameters which make them very flexible for approximating empirical distributions. A hybrid Markov chain Monte Carlo method is then studied to sample the unknown parameters of APDs. The generated samples can be used to compute the Bayesian estimators of the unknown APD parameters. Numerical experiments show the good performance of the proposed estimation method. An application to an image segmentation problem is finally investigated.","keywords":"image segmentation;Markov processes;Monte Carlo methods;parameter estimation;Bayesian parameter estimation;asymmetric power distributions;APD parameter;hybrid Markov chain Monte Carlo method;image segmentation;Bayes methods;Image segmentation;Shape;Markov processes;Histograms;Estimation;Europe;Asymmetric power distributions;hierarchical Bayesian model;MCMC;Gibbs sampler;Image segmentation","doi":"10.1109/EUSIPCO.2015.7362776","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570102961.pdf","bibtex":"@InProceedings{7362776,\n author = {A. Baussard and J. Tourneret},\n booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},\n title = {Bayesian parameter estimation for asymmetric power distributions},\n year = {2015},\n pages = {2206-2210},\n abstract = {This paper proposes a hierarchical Bayesian model for estimating the parameters of asymmetric power distributions (APDs). These distributions are defined by shape, scale and asymmetry parameters which make them very flexible for approximating empirical distributions. A hybrid Markov chain Monte Carlo method is then studied to sample the unknown parameters of APDs. The generated samples can be used to compute the Bayesian estimators of the unknown APD parameters. Numerical experiments show the good performance of the proposed estimation method. An application to an image segmentation problem is finally investigated.},\n keywords = {image segmentation;Markov processes;Monte Carlo methods;parameter estimation;Bayesian parameter estimation;asymmetric power distributions;APD parameter;hybrid Markov chain Monte Carlo method;image segmentation;Bayes methods;Image segmentation;Shape;Markov processes;Histograms;Estimation;Europe;Asymmetric power distributions;hierarchical Bayesian model;MCMC;Gibbs sampler;Image segmentation},\n doi = {10.1109/EUSIPCO.2015.7362776},\n issn = {2076-1465},\n month = {Aug},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570102961.pdf},\n}\n\n","author_short":["Baussard, A.","Tourneret, J."],"key":"7362776","id":"7362776","bibbaseid":"baussard-tourneret-bayesianparameterestimationforasymmetricpowerdistributions-2015","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570102961.pdf"},"keyword":["image segmentation;Markov processes;Monte Carlo methods;parameter estimation;Bayesian parameter estimation;asymmetric power distributions;APD parameter;hybrid Markov chain Monte Carlo method;image segmentation;Bayes methods;Image segmentation;Shape;Markov processes;Histograms;Estimation;Europe;Asymmetric power distributions;hierarchical Bayesian model;MCMC;Gibbs sampler;Image segmentation"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2015url.bib","creationDate":"2021-02-13T17:31:52.540Z","downloads":0,"keywords":["image segmentation;markov processes;monte carlo methods;parameter estimation;bayesian parameter estimation;asymmetric power distributions;apd parameter;hybrid markov chain monte carlo method;image segmentation;bayes methods;image segmentation;shape;markov processes;histograms;estimation;europe;asymmetric power distributions;hierarchical bayesian model;mcmc;gibbs sampler;image segmentation"],"search_terms":["bayesian","parameter","estimation","asymmetric","power","distributions","baussard","tourneret"],"title":"Bayesian parameter estimation for asymmetric power distributions","year":2015,"dataSources":["eov4vbT6mnAiTpKji","knrZsDjSNHWtA9WNT"]}