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Volumn 1, Issue 1, 2014, Pages 120-128

Analyzing 2000–2010 Childhood Age-Adjusted Cancer Rates in Florida: A Spatial Clustering Approach

Author keywords

Bayesian hierarchical models; Epidemiology; Marginal likelihood; Pediatric cancers; Reversible jump MCMC

Indexed keywords


EID: 84957953730     PISSN: None     EISSN: 2330443X     Source Type: Journal    
DOI: 10.1080/2330443X.2014.979962     Document Type: Article
Times cited : (10)

References (12)
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    • Clustering Curves Based on Change Point Analysis: A Nonparametric Bayesian Approach
    • in press
    • Dass, S.C., Lim, C., Maiti, T., Zhang, Z., (in press), Clustering Curves Based on Change Point Analysis: A Nonparametric Bayesian Approach, Statistica Sinica. DOI: 10.5705/ss.2012.308.
    • Statistica Sinica
    • Dass, S.C.1    Lim, C.2    Maiti, T.3    Zhang, Z.4
  • 6
    • 54949111733 scopus 로고    scopus 로고
    • Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
    • Gramacy, R.B., Lee, H. K.H., (2008), Bayesian Treed Gaussian Process Models With an Application to Computer Modeling, Journal of the American Statistical Association, 103, 1119–1130.
    • (2008) Journal of the American Statistical Association , vol.103 , pp. 1119-1130
    • Gramacy, R.B.1    Lee, H.K.H.2
  • 7
    • 77956889087 scopus 로고
    • Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination
    • Green, P.J., (1995), Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination, Biometrika, 82, 711–732.
    • (1995) Biometrika , vol.82 , pp. 711-732
    • Green, P.J.1
  • 9
    • 1642602502 scopus 로고    scopus 로고
    • Bayesian Detection of Clusters and Discontinuities in Disease Maps
    • Knorr-Held, L., Raßer, G., (2000), Bayesian Detection of Clusters and Discontinuities in Disease Maps, Biometrics, 56, 13–21.
    • (2000) Biometrics , vol.56 , pp. 13-21
    • Knorr-Held, L.1    Raßer, G.2
  • 10
    • 84922990179 scopus 로고    scopus 로고
    • Adaptive Bayesian Nonstationary Modeling for Large Spatial Datasets Using Covariance Approximations
    • Konomi, B.A., Sang, H., Mallick, B.K., (2014), Adaptive Bayesian Nonstationary Modeling for Large Spatial Datasets Using Covariance Approximations, Journal of Computational and Graphical Statistics, 23, 802–829.
    • (2014) Journal of Computational and Graphical Statistics , vol.23 , pp. 802-829
    • Konomi, B.A.1    Sang, H.2    Mallick, B.K.3
  • 12
    • 85077552566 scopus 로고    scopus 로고
    • SEER*Stat Database, National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released June 2010. Underlying mortality data provided by NCHS
    • Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database, “Mortality—All COD, Aggregated With State, Total U.S. (1969–2007) ”, National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released June 2010. Underlying mortality data provided by NCHS (www.cdc.gov/nchs).
    • Mortality—All COD, Aggregated With State, Total U.S. (1969–2007)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.