Kernel Density Estimation for Demonstration Purposes
Overview
Demonstration code showing how (univariate) kernel density estimates are computed, at least conceptually, and allowing users to experiment with different kernels, should they so wish. The method used follows directly the definition, but gains efficiency by replacing the observations by frequencies in a very fine grid covering the sample range. A canonical reference is B. W. Silverman, (1998) <doi: 10.1201/9781315140919>. NOTE: the density function in the stats package uses a more sophisticated method based on the fast Fourier transform and that function should be used if computational efficiency is a prime consideration.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Bill Venables <Bill.Venables@gmail.com>’
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Authors@R: person(given = "Bill",
family = "Venables",
role = c("aut", "cre"),
email = "bill.venables@gmail.com")
as necessary.- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 3includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
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- Help pages citing references
- 67%
Downloads
Dependencies
Installing demoKde adds no packages beyond those that come with R.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
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- RR 4.0.0 released · 2020-04-24
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- RR 3.3.0 released · 2016-05-03
- RR 3.2.0 released · 2015-04-16
- RR 3.1.0 released · 2014-04-10
Package metadata
- First published
- 2013-10-20
- Total releases
- 5 / 13 yrs
- License
- GPL-2 OSI
- Download size
- 4.4 KB
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