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Bai Z, Hsing T.  Submitted.  The broken sample problem. Probability Theory and Related Fields.
Berliner LM.  2003.  Physical-statistical modeling in geophysics. Journal of Geophysical Research. 108(D24):8776,doi:10.1029/2002JD002865.
Berliner LM.  2000.  Hierarchical Bayesian modeling in the environmental sciences. Allgemeines Statistisches Archiv, Journal of the German Statistical Society. 84:141-153.
Berliner LM.  2003.  Uncertainty and climate change. Statistical Science. 18:430-435.
Berliner LM, Cressie N, Jezek K, Kim Y, Lam CQ.  2005.  Hierarchical Bayesian modeling of the movement of ice streams. Statistical Solutions to Modern Problems: Proceedings of the 20th International Workshop on Statistical Modelling, Sydney, Australia, July 10-15, 2005. :3-15.
Berliner LM, Levine RA, Shea DJ.  2000.  Bayesian climate change assessment. Journal of Climate. 13:3805-3820.
Berliner LM.  2001.  Monte Carlo based ensemble forecasting. Statistics and Computing. 11:269-275.
Berliner LM, Milliff RF, Wikle CK.  2003.  Bayesian hierarchical modeling of air-sea interaction. Journal of Geophysical Research. 108(C4):3104,doi:10.1029/2002JC001413.
Biswas S, Lin S.  2006.  A Bayesian approach for incorporating variable rates of heterogeneity in linkage analysis. Journal of the American Statistical Association. 101:1341-1351.
Biswas S, Papachristou C, Irwin M, Lin S.  2002.  Linkage analysis of the simulated data-comparison of methods. Proceedings of the Genetic Analysis Workshop. 13:372-276.
Blumenthal S, Dahiya RC.  2002.  Examples where the maximum likelihood estimator has small asymptotic efficiency. Proceedings of the Hawaii International Conference on Statistics and Related Fields.
Brock G, Pihur V, Kubatko LS.  2009.  Detecting gene regulatory networks from microarray data usig fuzzy logic. Fuzzy Systems in Bioinformatics and Computational Biology. pgs:141-164.
Brown LD, George EI, Xu X.  2008.  Admissible Predictive Density Estimation. Annals of Statistics. 36:1156-1170.
Browne MW, Zhang G.  2007.  Developments in the Factor Analysis of Individual Time Series. Factor Analysis at 100: Historical Developments and Future Directions.