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Using prior-data conflict to tune Bayesian regularized regression models

Statistics and Computing(2025)10.1007/s11222-025-10582-1Source: DataRank Database

Using prior-data conflict to tune Bayesian regularized regression models is a research paper published in Statistics and Computing (2025). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (6 grants)Impact (FWCI 0.00)OA: hybridTopics (30)IDs (PubMed, PMC, OpenAlex)SDGs (1)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (3)

Karen Kopciuk ORCID,Thierry Chekouo ORCID,Timofei Biziaev

Live enrichment

PubMed:39990592 PMC:PMC11842445 OpenAlex:https://openalex.org/W4407772483

Canadian Institutes of Health Research

Grant: PJT-148774

National Institute of General Medical Sciences

Grant: 1R35GM150537-01

Interpretable Bayesian Non-linear statistical learning models for multi-omics data integration

Natural Sciences and Engineering Research Council of Canada

Grant: RGPIN-2019-04810

NIGMS NIH HHS

Grant: R35 GM150537

Natural Sciences and Engineering Research Council of Canada

Grant: unidentified

unidentified

National Institutes of Health

Grant: 1F32GM013039-01

MOLECULAR ANALYSIS OF THE YEAST HEAT SHOCK TRANSCRIPTION

FWCI

0.00

Citation Percentile

0.0%

hybridLicense: cc-by-nc-nd

journalhttps://link.springer.com/content/pdf/10.1007/s11222-025-10582-1.pdf

HYBRIDhttps://doi.org/10.1007/s11222-025-10582-1

publisherhttps://link.springer.com/content/pdf/10.1007/s11222-025-10582-1.pdf

publisherhttps://link.springer.com/article/10.1007/s11222-025-10582-1/fulltext.html

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39990592

Fields of Study

Statistical Methods and InferenceStatistical Methods and Bayesian InferenceBayesian Methods and Mixture ModelsMedicineComputer ScienceMathematics0101 mathematics01 natural sciences

Keywords

Bayesian probabilityRegressionEconometricsComputer scienceBayesian linear regressionRegression analysisMathematicsArtificial intelligenceStatisticsBayesian inferenceMachine learningData miningMCMCHigh-dimensional DataBayesian Variable SelectionKullback–leibler DivergenceCovid-19Original PaperRidge regression; shrinkage estimators (Lasso)Kullback-Leibler divergenceComputational methods for problems pertaining to statisticsApplications of statistics to biology and medical sciences; meta analysis

Sustainable Development Goals

SDG 0: Climate action