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KernSmoothIRT

6.6Package record

Nonparametric Item Response Theory

0packages depend
3.3Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.

Install

Health

CRAN checks
13OK
Slowest check: 2.9 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-07-30
  • NOTE14 NOTE2026-04-22
  • ERROR13 NOTE, 1 ERROR2026-04-18
Show 1 earlier changeHide 1 earlier change
  • NOTE14 NOTE2026-03-10
Advisories

none known

Documentation

In release 6.6
READMENoVignettesNoNEWSNoCitation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Help pages
17includes a package overview page
Examples that run
100%1 run in a plain check
Exported functions with examples
8%
Documented parameters
100%
Return-value docs
15%
Help pages citing references
100%

Downloads

3.3K
CRAN downloads in the past year
Rank #10,610 · ~9/day · ~279/mo
Daily download trend is not available in this view yet.
34530 days
98490 days
3.3K1 year
Compare downloads with other packages →
Also on364 r2u1 autocran2.7K conda_forge92 c2d4u

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)

Installing KernSmoothIRT adds 30 packages (17 with compiled code, 25 MB of source tarballs). Heaviest: bslib 5.6 MB, rgl 4.0 MB, sass 2.9 MB.

Depends (0)
none
Imports (4)
LinkingTo (1)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (3)
Author, Maintainer since 1.0 (2011)
Releases (10)

Pick two releases to compare their code metrics.

  • 6.6Latest
    record
    2026-07-23 · current release · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 6.4
    record
    2020-02-17 · diff ↗
  • 6.3
    record
    2020-02-11 · diff ↗
  • unarchivedReturned to CRAN
    2019-08-21
  • 6.2
    record
    2019-08-21 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • archivedRemoved from CRAN
    2019-04-18
    check problems were not corrected despite reminders
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
Show 13 earlier eventsHide 13 earlier events
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • 6.1
    record
    2014-06-17 · diff ↗
  • R
    R 3.1.0 released · 2014-04-10
  • 6.0
    record
    2013-09-16 · diff ↗
  • R
    R 3.0.0 released · 2013-04-03
  • 5.0
    record
    2013-03-06 · diff ↗ ·
    added 13 exports
    itemcor, subjscore, subjthetaML, subjscoreML, subjOCC, print.ksIRT, plot.ksIRT, subjEIS, subjETS, PCA, subjOCCDIF, subjEISDIF, subjETSDIF
  • 3.0
    record
    2012-05-03 · diff ↗
  • R
    R 2.15.0 released · 2012-03-30
  • 2.0
    record
    2011-12-16 · diff ↗
  • R
    R 2.14.0 released · 2011-10-31
  • 1.0
    record
    2011-08-19
  • R
    R 2.13.0 released · 2011-04-13

Package metadata

First published
2011-08-19
Total releases
10 / 15 yrs
License
GPL-2 OSI
Bundled data
83 KB / 6 files
Download size
70 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("KernSmoothIRT")

The package provides a citation file, so citation() returns the authors' own entry.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for KernSmoothIRT version 6.6 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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