Home ›
Entities
› academia
› Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size
Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size
Research article (Bioinformatics, 2019) · cited 37× · AI/ML
Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size
Summary
Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size is a scholarly article[1].
Key Facts
Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size. Retrieved May 24, 2026, from https://4ort.xyz/entity/benefits-of-dimension-reduction-in-penalized-regression-methods-for-high-dimensional-grouped-data-a-case-study-in-low-sa
MLA“Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/benefits-of-dimension-reduction-in-penalized-regression-methods-for-high-dimensional-grouped-data-a-case-study-in-low-sa.
BibTeX@misc{4ortxyz_benefits-of-dimension-reduction-in-penalized-regression-methods-for-high-dimensional-grouped-data-a-case-study-in-low-sa_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size}}, year = {2026}, url = {https://4ort.xyz/entity/benefits-of-dimension-reduction-in-penalized-regression-methods-for-high-dimensional-grouped-data-a-case-study-in-low-sa}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Benefits of dimension reduction in penalized regression methods for high-dimensional grouped data: a case study in low sample size — https://4ort.xyz/entity/benefits-of-dimension-reduction-in-penalized-regression-methods-for-high-dimensional-grouped-data-a-case-study-in-low-sa (retrieved 2026-05-24)
