Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates
Doss, Hani
Ann. Statist., Tome 13 (1985) no. 1, p. 1432-1444 / Harvested from Project Euclid
Let $X_i, i = 1, \ldots, n$ be i.i.d. $\sim F_\theta$, where $F_\theta(x) = F(x - \theta)$ for some $F$ that has median equal to 0. $F$ is assumed unknown or only partially known, and the problem is to estimate $\theta$. Priors are put on the pair $(F, \theta)$. The priors on $F$ concentrate all their mass on c.d.f.s with median equal to 0. These priors include "Dirichlet-type" priors. The marginal posterior distribution of $\theta$ given $X_1, \ldots, X_n$ is computed. The mean of the posterior is taken as the estimate of $\theta$.
Publié le : 1985-12-14
Classification:  Bayes estimator,  Dirichlet process priors,  estimation of the median,  estimation of quantiles,  regular conditional distribution,  62F15,  62G05
@article{1176349746,
     author = {Doss, Hani},
     title = {Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates},
     journal = {Ann. Statist.},
     volume = {13},
     number = {1},
     year = {1985},
     pages = { 1432-1444},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176349746}
}
Doss, Hani. Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates. Ann. Statist., Tome 13 (1985) no. 1, pp.  1432-1444. http://gdmltest.u-ga.fr/item/1176349746/