Package: deamer
Type: Package
Title: Deconvolution density estimation with adaptive methods for a
        variable prone to measurement error
Version: 1.0
Date: 2012-07-03
Author: Julien Stirnemann, Adeline Samson, Fabienne Comte. Contribution
        from Claire Lacour.
Maintainer: j.stirnemann <j.stirnemann@gmail.com>
Description: deamer provides deconvolution algorithms for the
        non-parametric estimation of the density f of an error-prone
        variable x with additive noise e. The model is y = x + e where
        the noisy variable y is observed, while x is unobserved.
        Estimation may be performed for i) a known density of the error
        ii) with an auxiliary sample of pure noise and iii) with an
        auxiliary sample of replicate (repeated) measurements.
        Estimation is performed using adaptive model selection and
        penalized contrasts.
License: GPL
Packaged: 2012-08-04 18:18:07 UTC; Joe
Repository: CRAN
Date/Publication: 2012-08-05 06:07:55
Built: R 3.1.0; ; 2013-10-24 14:42:19 UTC; unix
