메뉴 건너뛰기




Volumn , Issue , 2013, Pages 149-170

Bayesian smoothing, shrinkage and variable selection in hazard regression

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION; HAZARDS; INTELLIGENT SYSTEMS; ITERATIVE METHODS; MARKOV PROCESSES; MIXTURES; MONTE CARLO METHODS; SHRINKAGE;

EID: 84938292491     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-642-35494-6_10     Document Type: Chapter
Times cited : (5)

References (31)
  • 1
    • 19944372078 scopus 로고    scopus 로고
    • Simulating survival times for Cox regression models
    • Bender, R., Augustin, T., & Blettner, M. (2005). Simulating survival times for Cox regression models. Statistics in Medicine, 24, 1713-1723.
    • (2005) Statistics in Medicine , vol.24 , pp. 1713-1723
    • Bender, R.1    Augustin, T.2    Blettner, M.3
  • 2
    • 77952566299 scopus 로고    scopus 로고
    • High-dimensional Cox models: The choice of penalty as part of the model building process
    • Benner, A., Zucknick, M., Hielscher, T., Ittrich, C., & Mansmann, U. (2010). High-dimensional Cox models: the choice of penalty as part of the model building process. Biometrical Journal, 52, 50-69.
    • (2010) Biometrical Journal , vol.52 , pp. 50-69
    • Benner, A.1    Zucknick, M.2    Hielscher, T.3    Ittrich, C.4    Mansmann, U.5
  • 3
    • 26444547624 scopus 로고    scopus 로고
    • Generalized additive regression based on Bayesian P-splines
    • Brezger, A., & Lang, S. (2006). Generalized additive regression based on Bayesian P-splines. Computational Statistics & Data Analysis, 50, 967-991.
    • (2006) Computational Statistics & Data Analysis , vol.50 , pp. 967-991
    • Brezger, A.1    Lang, S.2
  • 5
    • 77953326052 scopus 로고    scopus 로고
    • Bayesian regularisation in structured additive regression: A unifying perspective on shrinkage, smoothing and predictor selection
    • Fahrmeir, L., Kneib, T., & Konrath, S. (2010). Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection. Statistics and Computing, 20, 203-219.
    • (2010) Statistics and Computing , vol.20 , pp. 203-219
    • Fahrmeir, L.1    Kneib, T.2    Konrath, S.3
  • 6
    • 0036117466 scopus 로고    scopus 로고
    • Variable selection for Cox's proportional hazards model and frailty model
    • Fan, J., & Li, R. (2002). Variable selection for Cox's proportional hazards model and frailty model. The Annals of Statistics, 30, 74-99.
    • (2002) The Annals of Statistics , vol.30 , pp. 74-99
    • Fan, J.1    Li, R.2
  • 8
    • 0031526204 scopus 로고    scopus 로고
    • Approaches for Bayesian variable selection
    • George, E. I., & McCulloch, R. E. (1997). Approaches for Bayesian variable selection. Statistica Sinica, 7, 339-373.
    • (1997) Statistica Sinica , vol.7 , pp. 339-373
    • George, E.I.1    McCulloch, R.E.2
  • 9
    • 77952568988 scopus 로고    scopus 로고
    • L1-penalized estimation in the Cox proportional hazards model
    • Goeman, J. J. (2010). L1-penalized estimation in the Cox proportional hazards model. Biometrical Journal, 52, 70-84.
    • (2010) Biometrical Journal , vol.52 , pp. 70-84
    • Goeman, J.J.1
  • 10
    • 0033619170 scopus 로고    scopus 로고
    • Assessment and comparison of prognostic classification schemes for survival data
    • Graf, E., Schmoor, C., Sauerbrei, W., & Schumacher, M. (1999). Assessment and comparison of prognostic classification schemes for survival data. Statistics in Medicine, 18, 2529-2545.
    • (1999) Statistics in Medicine , vol.18 , pp. 2529-2545
    • Graf, E.1    Schmoor, C.2    Sauerbrei, W.3    Schumacher, M.4
  • 14
    • 0042744696 scopus 로고    scopus 로고
    • Detecting differentially expressed genes in microarrays using Bayesian model selection
    • Ishwaran, H., & Rao, S. J. (2003). Detecting differentially expressed genes in microarrays using Bayesian model selection. Journal of the American Statistical Association, 98, 438-455.
    • (2003) Journal of the American Statistical Association , vol.98 , pp. 438-455
    • Ishwaran, H.1    Rao, S.J.2
  • 15
    • 22944460748 scopus 로고    scopus 로고
    • Spike and slab variable selection: Frequentist and Bayesian strategies
    • Ishwaran, H., & Rao, S. J. (2005). Spike and slab variable selection: frequentist and Bayesian strategies. The Annals of Statistics, 33, 730-773.
    • (2005) The Annals of Statistics , vol.33 , pp. 730-773
    • Ishwaran, H.1    Rao, S.J.2
  • 17
  • 19
    • 79551657781 scopus 로고    scopus 로고
    • The Bayesian elastic net
    • Li, Q., & Lin, N. (2010). The Bayesian elastic net. Bayesian Analysis, 5, 847-866.
    • (2010) Bayesian Analysis , vol.5 , pp. 847-866
    • Li, Q.1    Lin, N.2
  • 20
    • 37649024897 scopus 로고    scopus 로고
    • On the Breslow estimator
    • Lin, D. Y. (2007). On the Breslow estimator. Lifetime Data Analysis, 13, 471-480.
    • (2007) Lifetime Data Analysis , vol.13 , pp. 471-480
    • Lin, D.Y.1
  • 21
    • 57449103508 scopus 로고    scopus 로고
    • An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia
    • Metzeler, K. H., Hummel, M., Bloomfield, C. D., Spiekermann, K., Braess, J., et al. (2008). An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia. Blood, 112, 4193-4201.
    • (2008) Blood , vol.112 , pp. 4193-4201
    • Metzeler, K.H.1    Hummel, M.2    Bloomfield, C.D.3    Spiekermann, K.4    Braess, J.5
  • 22
    • 39149101409 scopus 로고    scopus 로고
    • Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models
    • Panagiotelis, A., & Smith, M. (2008). Bayesian identification, selection and estimation of semiparametric functions in high-dimensional additive models. Journal of Econometrics, 143, 291-316.
    • (2008) Journal of Econometrics , vol.143 , pp. 291-316
    • Panagiotelis, A.1    Smith, M.2
  • 26
    • 84871993172 scopus 로고    scopus 로고
    • Spike-and-slab priors for function selection in structured additive regression models
    • Scheipl, F., Fahrmeir, L., & Kneib, T. (2012). Spike-and-slab priors for function selection in structured additive regression models. Journal of the American Statistical Association. doi:10. 1080/01621459.2012.737742
    • (2012) Journal of the American Statistical Association
    • Scheipl, F.1    Fahrmeir, L.2    Kneib, T.3
  • 27
    • 3843102445 scopus 로고    scopus 로고
    • A Bayesian justification of Cox's partial likelihood
    • Sinha, D., Ibrahim, J. G., & Chen, M. H. (2003). A Bayesian justification of Cox's partial likelihood. Biometrika, 90, 629-641.
    • (2003) Biometrika , vol.90 , pp. 629-641
    • Sinha, D.1    Ibrahim, J.G.2    Chen, M.H.3
  • 28
    • 0000824232 scopus 로고    scopus 로고
    • Nonparametric regression using Bayesian variable selection
    • Smith, M., & Kohn, R. (1996). Nonparametric regression using Bayesian variable selection. Journal of Econometrics, 75, 317-343.
    • (1996) Journal of Econometrics , vol.75 , pp. 317-343
    • Smith, M.1    Kohn, R.2
  • 29
    • 0031015557 scopus 로고    scopus 로고
    • The lasso method for variable selection in the Cox model
    • Tibshirani, R. (1997). The lasso method for variable selection in the Cox model. Statistics in Medicine, 16, 385-395.
    • (1997) Statistics in Medicine , vol.16 , pp. 385-395
    • Tibshirani, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.