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OLS Field Name OLS Field Data
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
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NTIS  PB-220 354 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. 06/23/1988
Collation 123p
Abstract 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)
PUB Date Free Form Jan 73,
Category Codes 8H; 12A; 64H; 72F
NTIS Prices PC A06/MF A01
Document Type NT
Cataloging Source NTIS/MT
Control Number 326562170
Origin NTIS
Type CAT