Bayesian Estimation of The Ex-Gaussian Distribution
| Autor: | Abir El Haj, Yousri Slaoui, Clara Solier, Cyril Perret |
|---|---|
| Přispěvatelé: | Université de Poitiers - Faculté de Sciences fondamentales et appliquées, Université de Poitiers, Laboratoire de Mathématiques et Applications (LMA-Poitiers), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Maison des sciences de l'homme et de la société de Poitiers (MSHS), Centre de Recherches sur la Cognition et l'Apprentissage (CeRCA), Université de Poitiers-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Université de Poitiers - UFR Sciences Humaines et Arts (Poitiers UFR SHA), Axe 1 (2017-2021) : 'Langage et apprentissage : corpus, cognition, genèse des œuvres ' (MSHS Poitiers), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Control and Optimization [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] Artificial Intelligence [SCCO.PSYC]Cognitive science/Psychology Signal Processing Computer Vision and Pattern Recognition Statistics Probability and Uncertainty Statistics::Computation Information Systems |
| Zdroj: | Statistics, Optimization and Information Computing Statistics, Optimization and Information Computing, International Academic Press, 2021, 9 (4), pp.809-819. ⟨10.19139/soic-2310-5070-1251⟩ |
| ISSN: | 2310-5070 2311-004X |
| DOI: | 10.19139/soic-2310-5070-1251 |
| Popis: | International audience; Fitting of the exponential modified Gaussian distribution to model reaction times and drawing conclusions from its estimated parameter values is one of the most popular method used in psychology. This paper aims to develop a Bayesian approach to estimate the parameters of the ex-Gaussian distribution. Since the chosen priors yield to posterior densities that are not of known form and that they are not always log-concave, we suggest to use the adaptive rejection Metropolis sampling method. Applications on simulated data and on real data are provided to compare this method to the standard maximum likelihood estimation method as well as the quantile maximum likelihood estimation. Results shows the effectiveness of the proposed Bayesian method by computing the root mean square error of the estimated parameters using the three methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|