Asymptotic normality in mixture models

Sara Van De Geer

ESAIM: Probability and Statistics (2010)

  • Volume: 1, page 17-33
  • ISSN: 1292-8100

Abstract

top
We study the estimation of a linear integral functional of a distribution F, using i.i.d. observations which density is a mixture of a family of densities k(.,y) under F. We examine the asymptotic distribution of the estimator obtained by plugging the non parametric maximum likelihood estimator (NPMLE) of F in the functional. A problem here is that usually, the NPMLE does not dominate F.
Our main aim here is to show that this can be overcome by considering a convex combination of F and the NPMLE.

How to cite

top

Sara Van De Geer. "Asymptotic normality in mixture models." ESAIM: Probability and Statistics 1 (2010): 17-33. <http://eudml.org/doc/197751>.

@article{SaraVanDeGeer2010,
abstract = { We study the estimation of a linear integral functional of a distribution F, using i.i.d. observations which density is a mixture of a family of densities k(.,y) under F. We examine the asymptotic distribution of the estimator obtained by plugging the non parametric maximum likelihood estimator (NPMLE) of F in the functional. A problem here is that usually, the NPMLE does not dominate F.
Our main aim here is to show that this can be overcome by considering a convex combination of F and the NPMLE. },
author = {Sara Van De Geer},
journal = {ESAIM: Probability and Statistics},
keywords = {Asymptotic efficiency / asymptotic normality / differentiable functionals / maximum likelihood / mixture model.; Asymptotic efficiency; asymptotic normality; differentiable functionals; linear integral functional; mixture model; nonparametric maximum likelihood estimator; NPMLE},
language = {eng},
month = {3},
pages = {17-33},
publisher = {EDP Sciences},
title = {Asymptotic normality in mixture models},
url = {http://eudml.org/doc/197751},
volume = {1},
year = {2010},
}

TY - JOUR
AU - Sara Van De Geer
TI - Asymptotic normality in mixture models
JO - ESAIM: Probability and Statistics
DA - 2010/3//
PB - EDP Sciences
VL - 1
SP - 17
EP - 33
AB - We study the estimation of a linear integral functional of a distribution F, using i.i.d. observations which density is a mixture of a family of densities k(.,y) under F. We examine the asymptotic distribution of the estimator obtained by plugging the non parametric maximum likelihood estimator (NPMLE) of F in the functional. A problem here is that usually, the NPMLE does not dominate F.
Our main aim here is to show that this can be overcome by considering a convex combination of F and the NPMLE.
LA - eng
KW - Asymptotic efficiency / asymptotic normality / differentiable functionals / maximum likelihood / mixture model.; Asymptotic efficiency; asymptotic normality; differentiable functionals; linear integral functional; mixture model; nonparametric maximum likelihood estimator; NPMLE
UR - http://eudml.org/doc/197751
ER -

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.