From 795f654b2a0593d2a09273fc7e39d7258c87d548 Mon Sep 17 00:00:00 2001 From: Aniket Patil Date: Mon, 14 Dec 2020 21:57:33 -0500 Subject: gnu: Add r-decon. * gnu/packages/cran.scm (r-decon): New variable. Signed-off-by: Leo Famulari --- gnu/packages/cran.scm | 38 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 38 insertions(+) (limited to 'gnu/packages') diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 45703792ed..157ac82fd0 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -32,6 +32,7 @@ ;;; Copyright © 2020 Arun Isaac ;;; Copyright © 2020 Magali Lemes ;;; Copyright © 2020 Simon Tournier +;;; Copyright © 2020 Aniket Patil ;;; ;;; This file is part of GNU Guix. ;;; @@ -25174,6 +25175,43 @@ orthogonal coordinate systems: cartesian, polar, spherical, cylindrical, parabolic or user defined by custom scale factors.") (license license:gpl3))) +(define-public r-decon + (package + (name "r-decon") + (version "1.2-4") + (source + (origin + (method url-fetch) + (uri (cran-uri "decon" version)) + (sha256 + (base32 + "1v4l0xq29rm8mks354g40g9jxn0didzlxg3g7z08m0gvj29zdj7s")))) + (properties `((upstream-name . "decon"))) + (build-system r-build-system) + (native-inputs + `(("gfortran" ,gfortran))) + (home-page + "https://cran.r-project.org/web/packages/decon/") + (synopsis "Deconvolution Estimation in Measurement Error Models") + (description + "This package contains a collection of functions to deal with +nonparametric measurement error problems using deconvolution +kernel methods. We focus two measurement error models in the +package: (1) an additive measurement error model, where the +goal is to estimate the density or distribution function from +contaminated data; (2) nonparametric regression model with +errors-in-variables. The R functions allow the measurement errors +to be either homoscedastic or heteroscedastic. To make the +deconvolution estimators computationally more efficient in R, +we adapt the \"Fast Fourier Transform\" (FFT) algorithm for +density estimation with error-free data to the deconvolution +kernel estimation. Several methods for the selection of the +data-driven smoothing parameter are also provided in the package. +See details in: Wang, X.F. and Wang, B. (2011). Deconvolution +estimation in measurement error models: The R package decon. +Journal of Statistical Software, 39(10), 1-24.") + (license license:gpl3+))) + (define-public r-aws-signature (package (name "r-aws-signature") -- cgit v1.2.3