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Main Title Bayesian Approach to Autocorrelation Estimation in Hydrologic Autoregressive Models.
Author Lento, Roberto L. ; Rodriguez-Iturb, Ignacio ; Schaake, J, John C. ;
CORP Author Massachusetts Inst. of Tech., Cambridge. Ralph M. Parsons Lab. for Water Resources and Hydrodynamics.
Year Published 1973
Report Number Rept. nos. ;R163 ;R73-14; DI-14-31-0001-9021; MIT-DSR-80628 ;OWRR-C-4118(9021); 09120,; C-4118(9021)(1)
Stock Number PB-220 354
Additional Subjects ( Hydrology ; Autocorrelation) ; Bayes theorem ; Monte Carlo method ; Probability distribution functions ; Mathematical models ; Time series analysis ; Bayesian estimation ; Maximum likelihood estimation
Library Call Number Additional Info Location Last
NTIS  PB-220 354 Some EPA libraries have a fiche copy filed under the call number shown. 07/26/2022
Collation 123p
Three general approaches leading to the marginal posterior probability distribution function for the autocorrelation coefficient of the first order annual autoregressive model are presented, based on varying assumptions about the incidental parameters of the model. The performance of the Bayes estimators for the quadratic, symmetric, linear and asymmetric linear loss functions is evaluated by Monte Carlo methods, and compared to the performance of some classical estimators, under the expected risk criterion and for conditions of limited data. The robustness of the Bayes estimator under changes of the loss function is also determined. The general framework for the derivation of a loss function for a hydrologic design problem is presented. (Author)