R/packagedocumentation.R

#' Deconvolution Tools for Measurement Error Problems
#' 
#' This package provides tools for performing non-parametric deconvolution on 
#' measurement error problems. It contains functions for finding bandwidths,
#' deconvolved densities and non-parametric regression estimates.
#' 
#' @name deconvolve-package
#' @docType package 
#' @author Aurore Delaigle, Timothy Hyndman, and Tianying Wang
#' 
#' @references 
#' Stefanski, L. and Carroll, R.J. (1990). Deconvoluting kernel density
#' estimators. \emph{Statistics}, 21, 2, 169-184.
#' 
#' Fan,  J.,  and Truong,  Y. K. (1993),  Nonparametric Regression With Errors
#' in Variables,  \emph{The Annals of Statistics}.  21,  1900-1925.
#' 
#' Carroll, R. J., Ruppert, D., and Stefanski, L. A. (1995). Measurement Error 
#' in Nonlinear Models: A Modern Perspective, Second Edition. Chapman Hall, New
#' York.
#' 
#' Delaigle, A. and Gijbels, I. (2002). Estimation of integrated squared density
#' derivatives from a contaminated sample. \emph{Journal of the Royal
#' Statistical Society, B}, 64, 4, 869-886.
#' 
#' Delaigle, A. and Gijbels, I. (2004). Practical bandwidth selection in
#' deconvolution kernel density estimation. \emph{Computational Statistics and
#' Data Analysis}, 45, 2, 249 - 267.
#' 
#' Delaigle, A. and Gijbels, I. (2007). Frequent problems in calculating 
#' integrals and optimizing objective functions: a case study in density 
#' deconvolution. \emph{Statistics and Computing}, 17, 349-355.
#'
#' Delaigle, A., Hall, P., and Meister, A. (2008). On Deconvolution with  
#' repeated measurements. \emph{Annals of Statistics}, 36, 665-685 
#'
#' Delaigle, A. and Hall, P. (2008). Using SIMEX for smoothing-parameter choice
#' in errors-in-variables problems. \emph{Journal of the American Statistical
#' Association}, 103, 481, 280-287
#' 
#' Delaigle, A. and Meister, A. (2008). Density estimation with heteroscedastic
#' error. \emph{Bernoulli}, 14, 2, 562-579.
#'
#' Delaigle, A. and Hall, P. (2016). Methodology for non-parametric
#' deconvolution when the error distribution is unknown. \emph{Journal of the
#' Royal Statistical Society: Series B (Statistical Methodology)}, 78, 1,
#' 231-252.
#' 
#' Camirand, F., Carroll, R.J., and Delaigle, A. (2018). Estimating the  
#' distribution of episodically consumed food measured with errors.  
#' \emph{Manuscript.} 
#' 
#' @keywords package
#' 
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TimothyHyndman/deconvolve documentation built on May 13, 2019, 11:51 p.m.