{ "id": "0810.4821", "version": "v1", "published": "2008-10-27T14:27:52.000Z", "updated": "2008-10-27T14:27:52.000Z", "title": "Estimation of distributions, moments and quantiles in deconvolution problems", "authors": [ "Peter Hall", "Soumendra N. Lahiri" ], "comment": "Published in at http://dx.doi.org/10.1214/07-AOS534 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)", "journal": "Annals of Statistics 2008, Vol. 36, No. 5, 2110-2134", "doi": "10.1214/07-AOS534", "categories": [ "math.ST", "stat.TH" ], "abstract": "When using the bootstrap in the presence of measurement error, we must first estimate the target distribution function; we cannot directly resample, since we do not have a sample from the target. These and other considerations motivate the development of estimators of distributions, and of related quantities such as moments and quantiles, in errors-in-variables settings. We show that such estimators have curious and unexpected properties. For example, if the distributions of the variable of interest, $W$, say, and of the observation error are both centered at zero, then the rate of convergence of an estimator of the distribution function of $W$ can be slower at the origin than away from the origin. This is an intrinsic characteristic of the problem, not a quirk of particular estimators; the property holds true for optimal estimators.", "revisions": [ { "version": "v1", "updated": "2008-10-27T14:27:52.000Z" } ], "analyses": { "subjects": [ "62G20", "62C20" ], "keywords": [ "deconvolution problems", "estimation", "target distribution function", "property holds true", "first estimate" ], "tags": [ "journal article" ], "publication": { "publisher": "Institute of Mathematical Statistics", "journal": "Ann. Stat." }, "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable", "adsabs": "2008arXiv0810.4821H" } } }