deamer (1.0)
Deconvolution density estimation with adaptive methods for a variable prone to measurement error.
http://cran.r-project.org/web/packages/deamer
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.
Maintainer:
j.stirnemann
Author(s): Julien Stirnemann, Adeline Samson, Fabienne Comte. Contribution from Claire Lacour.
License: GPL
Uses: Does not use any package
Released 11 months ago.
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