---
title: "bayesm (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to bayesm (R package) in their Crossref records, the first in 2018; most of them (2) in 2021."
url: https://scholar4ai.com/code/cran-bayesm
markdown_url: https://scholar4ai.com/code/cran-bayesm.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to bayesm (R package) in their Crossref records, the first in 2018; most of them (2) in 2021. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# bayesm (R package): papers linking to it

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

- CRAN
- https://CRAN.R-project.org/package=bayesm

All repositories: https://scholar4ai.com/code.md

## Key findings

- 5 papers in the tracked journals link to bayesm (R package) in their Crossref records, the first in 2018; most of them (2) in 2021.
- By category: Health Economics and Policy (1), Management (1) and Marketing (1); the journals with the most are PharmacoEconomics (1), Journal of Business Economics (1) and Journal of Marketing Analytics (1).

## By year

*Papers linking to bayesm (R package) by publication year*

| Year | Papers |
|---|---:|
| 2018 | 1 |
| 2021 | 2 |
| 2022 | 1 |
| 2023 | 1 |

## Journals

*Journals whose papers link to bayesm (R package) most*

| Journal | Papers |
|---|---:|
| [PharmacoEconomics](https://scholar4ai.com/journals/pharmacoeconomics.md) | 1 |
| [Journal of Business Economics](https://scholar4ai.com/journals/journal-of-business-economics.md) | 1 |
| [Journal of Marketing Analytics](https://scholar4ai.com/journals/journal-of-marketing-analytics.md) | 1 |
| [Information Systems and e-Business Management](https://scholar4ai.com/journals/information-systems-and-e-business-management.md) | 1 |
| [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | 1 |

## Papers

*Papers linking to bayesm (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2021-05-08 | [Understanding augmented reality adoption trade-offs in production environments from the perspective of future employees: A choice-based conjoint study](https://doi.org/10.1007/s10257-021-00529-0) | [Information Systems and e-Business Management](https://scholar4ai.com/journals/information-systems-and-e-business-management.md) | Julian Schuir, Frank Teuteberg | 26 | cites it |
| 2018-07-20 | [Severity-Stratified Discrete Choice Experiment Designs for Health State Evaluations](https://doi.org/10.1007/s40273-018-0694-6) | [PharmacoEconomics](https://scholar4ai.com/journals/pharmacoeconomics.md) | Sesil Lim, Marcel F. Jonker, Mark Oppe et al. | 19 | cites it |
| 2023-06-26 | [Multimodal preference heterogeneity in choice-based conjoint analysis: a simulation study](https://doi.org/10.1007/s11573-023-01156-6) | [Journal of Business Economics](https://scholar4ai.com/journals/journal-of-business-economics.md) | Nils Goeken, Peter Kurz, Winfried J. Steiner | 10 | cites it |
| 2021-06-10 | [Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming](https://doi.org/10.1057/s41270-021-00113-y) | [Journal of Marketing Analytics](https://scholar4ai.com/journals/journal-of-marketing-analytics.md) | John V. Colias, Stella Park, Elizabeth Horn | 9 | cites it |
| 2022-08-06 | [Seemingly unrelated clusterwise linear regression for contaminated data](https://doi.org/10.1007/s00362-022-01344-6) | [Statistical Papers](https://scholar4ai.com/journals/statistical-papers.md) | Gabriele Perrone, Gabriele Soffritti | 6 | 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). bayesm (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-bayesm

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

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).