wavethresh (R package): papers linking to it

CRAN · CRAN.R-project.org/package=wavethresh

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to wavethresh (R package) (https://CRAN.R-project.org/package=wavethresh), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

6 papers in the tracked journals link to wavethresh (R package) in their Crossref records, the first in 2016; most of them (2) in 2021.
By category: Statistics (5) and AI (1); the journals with the most are Statistics and Computing (2), Annals of the Institute of Statistical Mathematics (1) and Computational Statistics & Data Analysis (1).

By year#

20162025

Papers linking to wavethresh (R package) by publication year
Year	Papers
2016	1
2017	1
2019	1
2021	2
2025	1

Journals#

Journals whose papers link to wavethresh (R package) most
Journal	Papers
Statistics and Computing	2
Annals of the Institute of Statistical Mathematics	1
Computational Statistics & Data Analysis	1
Japanese Journal of Statistics and Data Science	1
Data Mining and Knowledge Discovery	1

Papers linking to wavethresh (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2021-02-17	A wavelet-based approach for imputation in nonstationary multivariate time series	Statistics and Computing	Rebecca Wilson, Idris Arthur Eckley, Matthew A. Nunes et al.	19	cites it
2017-02-13	Long memory and changepoint models: a spectral classification procedure	Statistics and Computing	Ben Norwood, Rebecca Killick	11	cites it
2016-10-07	Cross-validated wavelet block thresholding for non-Gaussian errors	Computational Statistics & Data Analysis	Kelly McGinnity, Roumen Varbanov, Eric Chicken	10	cites it
2019-02-20	Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series	Data Mining and Knowledge Discovery	Rebecca Wilson, Idris Arthur Eckley, Matthew A. Nunes et al.	6	cites it
2021-03-13	Nonparametric regression with warped wavelets and strong mixing processes	Annals of the Institute of Statistical Mathematics	Luz Marina Gómez Gómez, Rogério F. Porto, Pedro A. Morettin	3	cites it
2025-12-08	Parsimonious modeling of periodic time series using Fourier and wavelet techniques	Japanese Journal of Statistics and Data Science	Rhea Davis, Narayana Balakrishna	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). wavethresh (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-wavethresh

@misc{scholar4ai-code-cran-wavethresh,
  author = {{Scholar4AI}},
  title = {wavethresh (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-wavethresh}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).