These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

145 related articles for article (PubMed ID: 26332240)

  • 1. Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas.
    Bedford T; Daneshkhah A; Wilson KJ
    Risk Anal; 2016 Apr; 36(4):792-815. PubMed ID: 26332240
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modeling Correlated Discrete Uncertainties in Event Trees with Copulas.
    Wang T; Dyer JS; Butler JC
    Risk Anal; 2016 Feb; 36(2):396-410. PubMed ID: 26178458
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Vine copula selection using mutual information for hydrological dependence modeling.
    Ni L; Wang D; Wu J; Wang Y; Tao Y; Zhang J; Liu J; Xie F
    Environ Res; 2020 Jul; 186():109604. PubMed ID: 32380245
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Bayesian bivariate survival analysis using the power variance function copula.
    Romeo JS; Meyer R; Gallardo DI
    Lifetime Data Anal; 2018 Apr; 24(2):355-383. PubMed ID: 28536818
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Vine Regression with Bayes Nets: A Critical Comparison with Traditional Approaches Based on a Case Study on the Effects of Breastfeeding on IQ.
    Cooke RM; Joe H; Chang B
    Risk Anal; 2022 Jun; 42(6):1294-1305. PubMed ID: 33580587
    [TBL] [Abstract][Full Text] [Related]  

  • 6. R-vine models for spatial time series with an application to daily mean temperature.
    Erhardt TM; Czado C; Schepsmeier U
    Biometrics; 2015 Jun; 71(2):323-32. PubMed ID: 25660495
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Discovering Low-Dimensional Descriptions of Multineuronal Dependencies.
    Mitskopoulos L; Onken A
    Entropy (Basel); 2023 Jul; 25(7):. PubMed ID: 37509973
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Mixed vine copula flows for flexible modeling of neural dependencies.
    Mitskopoulos L; Amvrosiadis T; Onken A
    Front Neurosci; 2022; 16():910122. PubMed ID: 36213754
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Copula diagnostics for asymmetries and conditional dependence.
    Chang B; Joe H
    J Appl Stat; 2020; 47(9):1587-1615. PubMed ID: 35707577
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Dependence modeling for recurrent event times subject to right-censoring with D-vine copulas.
    Barthel N; Geerdens C; Czado C; Janssen P
    Biometrics; 2019 Jun; 75(2):439-451. PubMed ID: 30549012
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Joint regression analysis of correlated data using Gaussian copulas.
    Song PX; Li M; Yuan Y
    Biometrics; 2009 Mar; 65(1):60-8. PubMed ID: 18510653
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Bivariate survival modeling: a Bayesian approach based on Copulas.
    Romeo JS; Tanaka NI; Pedroso-de-Lima AC
    Lifetime Data Anal; 2006 Jun; 12(2):205-22. PubMed ID: 16868839
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence.
    Nikoloulopoulos AK
    Stat Methods Med Res; 2017 Oct; 26(5):2270-2286. PubMed ID: 26265766
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Risk analysis in the brazilian stock market: copula-APARCH modeling for value-at-risk.
    Carvalho MM; Sáfadi T
    J Appl Stat; 2022; 49(6):1598-1610. PubMed ID: 35707117
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bayesian semiparametric analysis of recurrent failure time data using copulas.
    Meyer R; Romeo JS
    Biom J; 2015 Nov; 57(6):982-1001. PubMed ID: 26153049
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Meta-analysis for the comparison of two diagnostic tests-A new approach based on copulas.
    Hoyer A; Kuss O
    Stat Med; 2018 Feb; 37(5):739-748. PubMed ID: 29193212
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A D-vine copula-based model for repeated measurements extending linear mixed models with homogeneous correlation structure.
    Killiches M; Czado C
    Biometrics; 2018 Sep; 74(3):997-1005. PubMed ID: 29569339
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Novel pruning and truncating of the mixture of vine copula clustering models.
    Alanazi FA
    Sci Rep; 2022 Nov; 12(1):19815. PubMed ID: 36396705
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Gaussian mixture copulas for high-dimensional clustering and dependency-based subtyping.
    Kasa SR; Bhattacharya S; Rajan V
    Bioinformatics; 2020 Jan; 36(2):621-628. PubMed ID: 31368480
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Information bounds for Gaussian copulas.
    Hoff PD; Niu X; Wellner JA
    Bernoulli (Andover); 2014; 20(2):604-622. PubMed ID: 25313292
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.