discSurv (R package): papers linking to it

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

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to discSurv (R package) (https://CRAN.R-project.org/package=discSurv), 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#

5 papers in the tracked journals link to discSurv (R package) in their Crossref records, the first in 2017; most of them (1) in 2026.
By category: Statistics (4) and AI (1); the journals with the most are Econometrics and Statistics (2), Lifetime Data Analysis (2) and Data Mining and Knowledge Discovery (1).
3 of the papers build on one another: a later paper cites an earlier one that also links discSurv (R package).

By year#

20172026

Papers linking to discSurv (R package) by publication year
Year	Papers
2017	1
2018	1
2019	1
2020	1
2026	1

Journals#

Journals whose papers link to discSurv (R package) most
Journal	Papers
Econometrics and Statistics	2
Lifetime Data Analysis	2
Data Mining and Knowledge Discovery	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Discrimination measures for discrete time-to-event predictions Econometrics and Statistics, 2017
- Tree-based modeling of time-varying coefficients in discrete time-to-event models Lifetime Data Analysis, 2019 — cites the paper above
- Discrete-time survival forests with Hellinger distance decision trees Data Mining and Knowledge Discovery, 2020 — cites the paper above

Papers linking to discSurv (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2017-04-21	Discrimination measures for discrete time-to-event predictions	Econometrics and Statistics	Matthias C. Schmid, Gerhard Tutz, Thomas Welchowski	17	cites it
2019-11-11	Tree-based modeling of time-varying coefficients in discrete time-to-event models	Lifetime Data Analysis	Marie‐Therese Puth, Gerhard Tutz, Nils Heim et al.	17	cites it
2020-03-14	Discrete-time survival forests with Hellinger distance decision trees	Data Mining and Knowledge Discovery	Matthias C. Schmid, Thomas Welchowski, Marvin N. Wright et al.	11	cites it
2018-12-20	The effect of explanatory variables on income: A tool that allows a closer look at the differences in income	Econometrics and Statistics	Gerhard Tutz, Moritz Berger	2	cites it
2026-05-10	Reduction techniques for survival analysis	Lifetime Data Analysis	Johannes Piller, Léa Orsini, Simon Wiegrebe et al.	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). discSurv (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-discsurv

@misc{scholar4ai-code-cran-discsurv,
  author = {{Scholar4AI}},
  title = {discSurv (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-discsurv}},
  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).