Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

copula (R package): papers linking to it

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

← Code and data repositories cited in research papers

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

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Key findings#

  • 20 papers in the tracked journals link to copula (R package) in their Crossref records, the first in 2016; most of them (4) in 2020.
  • By category: Statistics (16), Economics (2) and Finance (1); the journals with the most are Statistics and Computing (3), Journal of Multivariate Analysis (3) and Computational Statistics (3).
  • 4 of the papers build on one another: a later paper cites an earlier one that also links copula (R package).

By year#

2016: 1 paper2017: 4 papers2018: 2 papers2019: 1 paper2020: 4 papers2022: 2 papers2023: 3 papers2024: 1 paper2025: 2 papers
20162025
Papers linking to copula (R package) by publication year
YearPapers
20161
20174
20182
20191
20204
20222
20233
20241
20252

Journals#

Journals whose papers link to copula (R package) most
JournalPapers
Statistics and Computing3
Journal of Multivariate Analysis3
Computational Statistics3
Statistical Papers2
Journal of Statistical Theory and Practice2

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.

Papers linking to copula (R package), most cited first
PublishedTitleJournalAuthorsCitationsLink
2016-12-01The empirical beta copulaJournal of Multivariate AnalysisJohan Segers, Masaaki Sibuya, Hideatsu Tsukahara76cites it
2017-11-01Compound unimodal distributions for insurance lossesInsurance Mathematics and EconomicsAntonio Punzo, Luca Bagnato, Antonello Maruotti73cites it
2017-01-05Testing the Gaussian and Student's t copulas in a risk management frameworkEconomic ModellingAlexandre Lourme, Frantz Maurer25cites it
2020-06-25Generalised joint regression for count data: a penalty extension for competitive settingsStatistics and ComputingHendrik van der Wurp, Andreas Groll, Thomas Kneib et al.18cites it
2017-02-23Some copula inference procedures adapted to the presence of tiesComputational Statistics & Data AnalysisIvan Kojadinovic A17cites it
2018-05-16Hierarchical Archimax copulasJournal of Multivariate AnalysisMarius Hofert, Raphaël Huser, Avinash Prasad14cites it
2020-05-09On tests for symmetry and radial symmetry of bivariate copulas towards testing for ellipticityComputational StatisticsMiriam Jaser, Aleksey Min12cites it
2020-01-03Goodness-of-fit test of copula functions for semi-parametric univariate time series modelsStatistical PapersShulin Zhang, Qian M. Zhou, Huazhen Lin10cites it
2018-06-05Simulation and evaluation of the distribution of interest rate riskComputational Management ScienceJohan Hagenbjörk, Jörgen Blomvall9cites it
2022-05-13Estimation in copula models with two-piece skewed margins using the inference for margins methodEconometrics and StatisticsJonas Baillien, Irène Gijbels, Anneleen Verhasselt7cites it
2020-11-26Pair-copula Models for Analyzing Family DataJournal of Statistical Theory and PracticeYihao Deng, Narasinga Rao Chaganty6cites it
2022-08-10Copula shrinkage and portfolio allocation in ultra-high dimensionsJournal of Economic Dynamics and ControlStanislav Anatolyev, Пырлик Владимир Николаевич6cites it
2017-04-26Smooth copula-based estimation of the conditional density function with a single covariateJournal of Multivariate AnalysisPaul Janssen, Jan W. H. Swanepoel, Noël Veraverbeke5cites it
2019-09-03Testing marginal homogeneity of a continuous bivariate distribution with possibly incomplete paired dataMetrikaDaniel Gaigall5cites it
2023-09-28Testing symmetry for bivariate copulas using Bernstein polynomialsStatistics and ComputingGuanjie Lyu, Mohamed Belalia4cites it
2023-01-20Moment-based density estimation of confidential micro-data: a computational statistics approachStatistics and ComputingBradley Wakefield, Yan‐Xia Lin, Rathindra Sarathy et al.2cites it
2023-03-29A novel copula-based approach for parametric estimation of univariate time series through its covariance decayStatistical PapersGuilherme Pumi A, Taiane Schaedler Prass, Sílvia R. C. Lopes2cites it
2025-01-16Independence tests based on the shape of the Standard Young TableauComputational StatisticsJesús Enrique García, Verónica Andrea González-López, María Magdalena Kcala Álvaro1cites it
2024-03-26U-statistics Based Tests for Marginal Hazard Rate Orderings of Two Dependent VariablesJournal of Statistical Theory and PracticeLeena Kulkarni, Sangita Kulathinal, Isha Dewan0cites it
2025-12-29Fast inference in copula models with categorical explanatory variables using the one-step procedureComputational StatisticsAlexandre Brouste‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌, Christophe Dutang, Lilit Hovsepyan et al.0cites 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). copula (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-copula

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

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