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MaxWiK

1.0.6Package record

Machine Learning Method Based on Isolation Kernel Mean Embedding

0packages depend
2Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Incorporates Approximate Bayesian Computation to get a posterior distribution and to select a model optimal parameter for an observation point. Additionally, the meta-sampling heuristic algorithm is realized for parameter estimation, which requires no model runs and is dimension-independent. A sampling scheme is also presented that allows model runs and uses the meta-sampling for point generation. A predictor is realized as the meta-sampling for the model output. All the algorithms leverage a machine learning method utilizing the maxima weighted Isolation Kernel approach, or 'MaxWiK'. The method involves transforming raw data to a Hilbert space (mapping) and measuring the similarity between simulated points and the maxima weighted Isolation Kernel mapping corresponding to the observation point. Comprehensive details of the methodology can be found in the papers Iurii Nagornov (2024) doi:10.1007/978-3-031-66431-1_16 and Iurii Nagornov (2023) doi:10.1007/978-3-031-29168-5_18.

Changes in 1.0.6

**2025 July 7th**

Update and fix of theme usage for ggplot2 package.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 3.2 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.6
READMEYes · 542 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 1.0.6Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
23 (14 internal)includes a package overview page
Examples that run
100%21 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%
Vignettes (1)

Downloads

2K
CRAN downloads in the past year
Rank #23,300 · ~6/day · ~170/mo
Daily download trend is not available in this view yet.
22830 days
55790 days
2K1 year
Compare downloads with other packages →
Also on63 r2u5 autocran

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)

Installing MaxWiK adds 23 packages (10 with compiled code, 20 MB of source tarballs). Heaviest: ggplot2 6.0 MB, abc.data 4.6 MB, isoband 1.5 MB.

Depends (1)
R >= 3.3.0
Imports (7)
methodsstatsutilsscalesparallelabcggplot2
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 1.0.5 (2024), Copyright holder
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.6Latest
    record
    2025-07-07 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.5
    record
    2024-11-25
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-11-25
Total releases
2 / 2 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.3.0
Bundled data
131 KB / 1 file
Download size
561 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MaxWiK")
Nagornov, Y. (2025). MaxWiK: Machine Learning Method Based on Isolation Kernel Mean Embedding (Version 1.0.6) [Computer software]. https://doi.org/10.32614/CRAN.package.MaxWiK

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 MaxWiK version 1.0.6 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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