Consistent Density Deconvolution under Partially Known Error Distribution
We estimate the distribution of a real-valued random variable from contaminated observations. The additive error is supposed to be normally distributed, but with unknown variance. The distribution is identifiable from the observations if we restrict the class of considered distributions by a simple condition in the time domain. A minimum distance estimator is shown to be consistent imposing only a slightly stronger assumption than the identification condition.
|Date of creation:||06 Oct 2009|
|Date of revision:|
|Contact details of provider:|| Phone: (+33) 5 61 12 86 23|
Web page: http://www.tse-fr.eu/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hall, P. & Simar, L., 2000.
"Estimating a Changepoint, Boundary of Frontier in the Presence of Observation Error,"
0012, Catholique de Louvain - Institut de statistique.
- Hall P. & Simar L., 2002. "Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 523-534, June.
- Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2011.
"Convergence Rates For Ill-Posed Inverse Problems With An Unknown Operator,"
Cambridge University Press, vol. 27(03), pages 522-545, June.
- Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2009. "Convergence Rates for III-Posed Inverse Problems with an Unknown Operator," TSE Working Papers 09-030, Toulouse School of Economics (TSE).
- Neumann, Michael H., 2007. "Deconvolution from panel data with unknown error distribution," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1955-1968, November.
- Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:22200. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.