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[bug#44033,2/3] gnu: Add r-locpol.

Message ID 20201016131338.62737-2-aniket112.patil@gmail.com
State New
Headers show
Series [bug#44033,1/3] gnu: Add r-decon. | expand


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Commit Message

Aniket Patil Oct. 16, 2020, 1:13 p.m. UTC
* gnu/packages/cran.scm (r-locpol): New variable.
 gnu/packages/cran.scm | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)
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diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index 0370cdd993..1529849211 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -24619,3 +24619,22 @@  absolute GSEA.")
       "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-locpol
+  (package
+    (name "r-locpol")
+    (version "0.7-0")
+    (source
+      (origin
+        (method url-fetch)
+        (uri (cran-uri "locpol" version))
+        (sha256
+          (base32
+            "1p915n0l09kbwkly627074jslxl01yssp1rf0c7sygvsw6sgy5lm"))))
+    (properties `((upstream-name . "locpol")))
+    (build-system r-build-system)
+    (home-page
+      "https://cran.r-project.org/web/packages/locpol")
+    (synopsis "Kernel Local Polynomial Regression")
+    (description
+      "Computes local polynomial estimators for the regression and also density.  It comprises several different utilities to handle kernel estimators.")
+    (license license:gpl2+)))